Brolly Academy | Snowflake
Snowflake Competitors
Databricks, Redshift, BigQuery, Fabric, Oracle, Teradata, ClickHouse and Firebolt Compared (2026)
A plain-English guide to Snowflake's main competitors in 2026: Databricks, Amazon Redshift, Google BigQuery, Microsoft Fabric, Oracle, Teradata, ClickHouse, Firebolt and open lakehouse stacks, grouped by type, with official pricing models, what each is best for, what makes Snowflake different, and what it all means for your data career in India.
Snowflake competitors compared for 2026: Databricks, Redshift, BigQuery, Microsoft Fabric, Oracle, Teradata, ClickHouse and Firebolt, with pricing models.
By Brolly Academy Team · Brolly Academy · Updated 24 October 2026
Table of Contents
1. Snowflake competitors at a glance
2. How Snowflake's competitors are grouped
6. Microsoft Fabric and Azure Synapse
7. Oracle Autonomous AI Database
8. Teradata Cloud (formerly VantageCloud)
11. Open lakehouse options (Apache Iceberg plus an engine)
13. What makes Snowflake different
14. How to choose between Snowflake and its competitors
15. Companies that are not like-for-like Snowflake rivals
Quick answer
Snowflake's main competitors are Databricks, Amazon Redshift, Google BigQuery and Microsoft Fabric, followed by Oracle Autonomous AI Database, Teradata Cloud, ClickHouse Cloud, Firebolt and open lakehouse stacks built on Apache Iceberg. They all store and query large amounts of data for analytics and AI, but they differ in billing, cloud support and the teams they suit. No single platform wins for everyone: the right choice depends on your cloud, your team's skills (SQL or Python and Spark) and your workload.
- Lakehouse rival: Databricks Data + AI Platform
- Cloud provider warehouses: Amazon Redshift (AWS), Google BigQuery (Google Cloud), Microsoft Fabric Data Warehouse (Azure)
- Enterprise incumbents: Oracle Autonomous AI Database, Teradata Cloud (formerly VantageCloud)
- Speed-focused engines: ClickHouse Cloud, Firebolt
- Open options: Apache Iceberg tables queried by engines such as Spark, Flink and Trino
Key takeaways
- Snowflake competes on three fronts: lakehouse platforms (Databricks), the cloud providers' own warehouses (Redshift, BigQuery, Fabric), and fast, cost-focused engines (ClickHouse, Firebolt).
- Every vendor bills in a different unit (credits, DBUs, RPUs, slots, capacity units, compute units), so compare total monthly cost on your own workload, not list prices.
- Snowflake's clearest differences are its separate storage, compute and services layers, its multi-cloud reach on AWS, Azure and Google Cloud, and data sharing without copying data.
- Open table formats such as Apache Iceberg mean most of these platforms can now read the same data, so "Snowflake or X" is often "Snowflake and X".
- For your career, SQL, data modelling, dbt and one cloud transfer across every platform here. Learn one platform deeply, then add a second.
1. Snowflake competitors at a glance
Short answer: Nine platforms come up again and again as Snowflake alternatives, and each one has a different type, pricing model and sweet spot.
This table is your map. The pricing models come from each vendor's own pricing or documentation page, checked on 25 October 2026. "Best for" is our plain-English summary of what each vendor says its product does, not a benchmark result.
If you are new to the platform itself, read our guide on what Snowflake does first. In two lines: Snowflake is a cloud data platform that keeps storage, compute and cloud services in separate layers, and it runs on Amazon Web Services, Microsoft Azure and Google Cloud (Snowflake documentation, October 2026). Everything below compares other platforms against that design.
2. How Snowflake's competitors are grouped
Short answer: Group the rivals into five buckets: the lakehouse, the cloud providers' warehouses, enterprise incumbents, speed-focused engines and open lakehouse stacks.
Most "Snowflake alternatives" lists put every product in one long list, but a real-time engine like ClickHouse solves a different problem from a full platform like Databricks. Grouping them shows who competes for which job:
- Lakehouse platforms: Databricks. A lakehouse combines a data lake (cheap files in cloud storage) with warehouse features such as transactions and governance.
- Cloud provider warehouses: Amazon Redshift, Google BigQuery and Microsoft Fabric (with Azure Synapse Analytics as its predecessor). Each is built by the cloud company itself, so it fits tightly with that cloud.
- Enterprise incumbents: Oracle and Teradata. Long-running enterprise warehouses are often built on these, and migrations from them to Snowflake show up in senior job descriptions at IT services firms and GCCs (global capability centres).
- Speed-focused engines: ClickHouse and Firebolt. These focus on fast queries for dashboards and apps, often with "scale to zero" billing.
- Open lakehouse stacks: data kept in an open table format such as Apache Iceberg in your own cloud storage, and queried by engines such as Spark, Flink or Trino.
3. Databricks
Short answer: Databricks is Snowflake's closest and most talked-about competitor, a lakehouse platform aimed at data engineering, data science and AI teams.
Databricks now calls its product the "Databricks Data + AI Platform" (Databricks product page, October 2026). It describes it as a lakehouse that mixes data-lake flexibility with warehouse reliability. Its key building blocks are:
- Delta Lake: the default table format for all operations on Databricks, which adds ACID transactions and time travel to files in cloud storage (Databricks documentation, October 2026). ACID means reads and writes stay correct even when many jobs run at once.
- Unity Catalog: governance for data and AI assets, covering permissions, lineage and auditing.
- SQL warehouses: compute for SQL users, sold as Databricks SQL.
- Apache Iceberg support: as a second open format alongside Delta.
- AI tools: Agent Bricks and Genie.
On pricing, Databricks' pricing page (October 2026) says it is pay as you go with per-second metering, no upfront cost and committed-use discounts. Usage is measured in DBUs. A DBU (Databricks Unit) is Databricks' "normalized unit of processing power". The price covers compute only: storage and networking are billed by your cloud provider.
Databricks says it was named a Leader in the 2025 Gartner Magic Quadrant for Cloud Database Management Systems for the fifth year in a row (Databricks blog, November 2025). Gartner does not endorse any vendor, and we could not verify Snowflake's own 2025 position.
Where Databricks tends to fit: teams that write a lot of Python and Spark, train machine learning models and want their data to stay in open files in their own cloud account. Where Snowflake tends to fit: SQL-first analytics teams that want a fully managed platform. Some companies run both.
Our Snowflake vs Databricks comparison goes deeper, with a side-by-side table and which to learn first.
4. Amazon Redshift
Short answer: Amazon Redshift is AWS's own cloud warehouse, and it competes with Snowflake mainly inside companies that are committed to AWS.
According to AWS's feature page (October 2026), Redshift stores data in columns with compression and zone maps. Its main options are:
- RA3 and Graviton-based RG instances: provisioned clusters where compute scales separately from Redshift Managed Storage.
- Redshift Serverless: capacity scales automatically to a performance target, so you do not size a cluster yourself.
- Concurrency scaling: adds temporary capacity when many users query at once.
- Zero-ETL integrations: bring data in from Aurora, RDS, DynamoDB and enterprise apps without building pipelines.
- Lake queries: read-only SQL on Iceberg, Hudi and Delta Lake tables in Amazon S3.
- AI: Redshift ML (SageMaker through SQL), Amazon Bedrock integration and Amazon Q for SQL generation.
AWS's Redshift pricing page (US East, N. Virginia, October 2026) lists provisioned clusters from $0.543 per hour, Serverless at $0.375 per RPU-hour (from $1.50 per hour), managed storage at $0.024 per GB-month and Redshift Spectrum at $5.00 per TB scanned. An RPU (Redshift Processing Unit) is the unit of Serverless capacity. New Serverless users get a $300 credit valid for 90 days. The page shows no Mumbai prices, so do not assume these numbers apply in India.
AWS is both a competitor and a partner. Snowflake itself runs on AWS, including the AWS Mumbai region, so a company can choose Snowflake and still be an AWS customer.
For architecture, pricing models and migration details, read our full Snowflake vs Redshift guide.
5. Google BigQuery
Short answer: Google BigQuery is Google Cloud's serverless analytics platform, and it competes with Snowflake by removing all server sizing.
Google describes BigQuery as a serverless data analytics platform with no instances to provision (Google Cloud BigQuery pricing, October 2026). You never pick a warehouse size. Instead, you choose one of two compute models:
- On-demand: you pay per TiB of data your queries process. The first 1 TiB each month is free, then it costs $6.25 per TiB in the US regions shown. A project gets up to about 2,000 concurrent slots. A slot is a unit of BigQuery compute.
- Capacity: you pay per slot-hour, either pay as you go with autoscaling or with 1-year and 3-year commitments.
Google lists Mumbai (asia-south1) and Delhi (asia-south2) as BigQuery regions on the same page. We could not map per-edition slot-hour prices cleanly, so we do not quote them.
Google says it is a Leader in the 2025 Gartner Magic Quadrant for Cloud DBMS for the sixth year in a row (Google Cloud blog, November 2025). As with Databricks, this is the vendor's own claim, and Gartner does not endorse vendors.
Snowflake vs BigQuery in one paragraph: BigQuery's on-demand model charges for data scanned, so a careless SELECT * on a huge table costs money even if it runs once. Snowflake charges for the time a virtual warehouse (a cluster of compute that runs your queries) is switched on, measured in credits. Neither model is cheaper in general. BigQuery suits teams on Google Cloud with spiky, unpredictable queries. Snowflake suits teams that want the same platform on more than one cloud.
6. Microsoft Fabric and Azure Synapse
Short answer: Microsoft Fabric is Microsoft's all-in-one analytics platform, and its Data Warehouse is the main Snowflake competitor in Microsoft and Power BI shops.
Microsoft's documentation (October 2026) describes Fabric Data Warehouse as an enterprise relational "lake warehouse", built mainly around T-SQL, the SQL dialect used by SQL Server. Key points:
- Data is stored as Delta tables (Parquet files plus a transaction log) in OneLake, Fabric's single data lake.
- Storage and compute are separate, and it supports full multi-table ACID transactions.
- Every Fabric Lakehouse gets a read-only SQL analytics endpoint.
- A Migration Assistant moves workloads from Azure Synapse Analytics, SQL Server and Teradata.
Azure Synapse Analytics was Microsoft's earlier warehouse, so for "Snowflake vs Synapse" searches the current Microsoft product to compare is usually Fabric.
Microsoft's Fabric pricing page (October 2026) uses a shared pool of Capacity Units (CUs) sold as F SKUs, from F2 (2 CUs) up to F8192, pay as you go or reserved for 1 or 3 years (Microsoft says this saves about 41%), with a one-minute minimum. OneLake storage is billed per GB per month in hot, cool and cold tiers. Per-CU-hour prices were not shown, so we do not quote them.
Where Fabric tends to fit: companies already using Power BI, SQL Server and Microsoft 365, especially where the team thinks in T-SQL. Snowflake also runs on Azure, including the Azure Central India (Pune) region, so Azure customers have both options.
7. Oracle Autonomous AI Database
Short answer: Oracle's Autonomous AI Database competes with Snowflake mostly inside companies that already run Oracle.
Oracle's documentation now calls the service "Autonomous AI Database" (Oracle documentation, October 2026). It describes a fully managed, self-governing database for transactions, AI and analytics that scales compute and storage without downtime. You may still see the older name Autonomous Data Warehouse (ADW) in older articles. We could not open Oracle's pricing pages for this post, so we do not quote its pricing unit or prices.
Why it matters to you: many large enterprises have years of Oracle data warehouses and PL/SQL code. When they modernise, some stay with Oracle's cloud and some move to another platform such as Snowflake. AmbitionBox lists PL/SQL among the top skills on its Snowflake Developer salary page (AmbitionBox, October 2026), a sign that Oracle skills sit close to Snowflake work.
8. Teradata Cloud (formerly VantageCloud)
Short answer: Teradata is a long-standing enterprise warehouse vendor, and today its managed cloud offer is presented as Teradata Cloud.
Teradata's VantageCloud page now describes "Teradata Cloud", a managed cloud version of its Autonomous Knowledge Platform (Teradata website, October 2026). It offers always-on compute plus on-demand elastic compute, and runs on AWS, Azure and Google Cloud. Pricing is by quote, with no unit stated publicly.
Teradata matters for Snowflake careers mainly because of migrations. In the job descriptions we read on 25 October 2026, a Deloitte Snowflake Architect role in Hyderabad asked for experience migrating from Teradata, Redshift and SQL Server (Deloitte listing on LinkedIn, October 2026). Microsoft's Fabric Migration Assistant also lists Teradata as a source. So if you have Teradata experience, it is an asset when moving into Snowflake, not a dead end.
9. ClickHouse Cloud
Short answer: ClickHouse Cloud is a fast analytics database that competes with Snowflake for real-time dashboards and event data, with usage-based billing that scales to zero.
ClickHouse's pricing page (October 2026) lists usage-based Basic, Scale and Enterprise plans. Compute is metered per minute and priced per compute-unit-hour, where one unit is 8 GiB of RAM plus 2 vCPUs. Idle compute scales to zero and there is no monthly minimum. As an example, the page shows AWS us-east-1 Enterprise at $0.39030 per unit-hour and $25.30 per TB-month of storage. A trial gives $300 of credits over 30 days with no card needed.
Where ClickHouse tends to fit: product analytics, logs, clickstreams and dashboards where users expect answers in a blink. Where Snowflake tends to fit: broader enterprise warehousing with governance, sharing and many teams on one platform. A team can also use both, with Snowflake as the main warehouse and a fast engine for one heavy dashboard workload.
10. Firebolt
Short answer: Firebolt is an analytics engine built for low-latency queries, and it competes with Snowflake on speed-sensitive and cost-sensitive workloads.
Firebolt's pricing page (October 2026) says compute is billed per second per engine. Engines use node types S to XL and can run 1 to 128 nodes. One example is a single S compute-optimised node at $0.92 per hour. Engines can scale to zero. Storage is passed through at $0.0264 per GB-month (about $27 per TB). New users get $200 of free credits. The same page says Firebolt is fully open source and can be self-hosted.
That makes Firebolt one answer to the search "open source alternative to Snowflake". Before you invest learning time in it, check how often it appears in Indian job listings.
11. Open lakehouse options (Apache Iceberg plus an engine)
Short answer: An open lakehouse keeps your data in an open format such as Apache Iceberg in your own cloud storage and lets several engines query it, and Snowflake now supports this model too.
Apache Iceberg is an open table format: a published way to store table data (Parquet files) and its metadata so that different engines can read and write the same table. Delta Lake, Databricks' default format, is a similar idea.
An open lakehouse usually looks like this:
- Your data sits as Parquet files in Amazon S3, Google Cloud Storage or Azure storage.
- An Iceberg catalog keeps track of tables, versions and schemas.
- One or more engines query those tables, for example Spark, Flink or Trino.
- Governance rules (who can see which rows and columns) are applied through the catalog.
The twist: this is not purely a Snowflake competitor any more. Snowflake supports Apache Iceberg tables, either with Snowflake as the catalog (full read and write, and Snowflake handles maintenance such as compaction) or with an external catalog such as AWS Glue. The data can stay in your own S3, GCS or Azure storage, and external engines can read Snowflake-managed Iceberg tables through the Horizon Iceberg REST Catalog API (Snowflake documentation, October 2026). Snowflake Horizon Catalog extends masking and row-access policies to Iceberg REST-compatible engines such as Spark, Flink and Trino.
One naming note: Snowflake Open Catalog, Snowflake's hosted service for the Apache Polaris catalog, is closed to new customers as of October 2026, and new customers are pointed to Horizon Catalog (Snowflake documentation, October 2026).
What this means: "open lakehouse vs Snowflake" is often a false choice. Many teams keep data in Iceberg and use Snowflake as one of several engines on top.
12. Pricing models compared
Short answer: Every platform uses a different billing unit, so you cannot compare list prices directly; compare the cost of running your own workload for a month.
Snowflake bills compute in Platform Credits (AI features use AI Credits) plus storage per TB per month. Warehouses bill per second after a 60-second minimum each time they start, a suspended warehouse uses no credits, and credits per hour double at each size, from 1 for X-Small to 512 for 6X-Large. Snowflake's Service Consumption Table effective 15 October 2026 lists on-demand prices in AWS US East (N. Virginia) of $2 (Standard), $3 (Enterprise), $4 (Business Critical) and $6 (Virtual Private Snowflake) per credit, and $23 per TB per month for storage. Prices vary by cloud, region and edition.
Three practical rules when comparing:
- Watch idle time. Snowflake, ClickHouse and Firebolt let compute suspend or scale to zero. A warehouse left running all night costs money on any platform.
- Watch scan-based pricing. On BigQuery on-demand, cost follows the data scanned, so partitioning and selecting only needed columns matter.
- Ignore "X times cheaper" claims. We found no independent benchmark we could verify.
None of these pages shows an official rupee price, and we do not quote Mumbai-specific prices for any platform.
13. What makes Snowflake different
Short answer: Snowflake stands out for its three-layer design, true multi-cloud reach, data sharing without copies and built-in AI.
These differences come from Snowflake's own documentation (October 2026):
- Three separate layers. Storage, compute and cloud services are separate. Each virtual warehouse is independent, so a heavy data-loading job does not slow down an analyst's dashboard. See our Snowflake architecture diagram post for the full picture.
- Micro-partitions handled for you. Snowflake stores tables in its own compressed columnar format, split automatically into micro-partitions (small storage blocks of about 50 to 500 MB of uncompressed data).
- Same platform on three clouds. Snowflake runs on AWS, Azure and Google Cloud. In India it lists two regions: AWS Mumbai (ap-south-1) and Azure Central India (Pune). There is no Google Cloud India region for Snowflake.
- Concurrency on demand. Multi-cluster warehouses (Enterprise Edition and above) add clusters automatically when many users query at once.
- Data sharing without copies. With Secure Data Sharing, a provider shares live tables with another account and no data is copied or moved. Listings on Snowflake Marketplace extend this to public and paid data products. Our data sharing in Snowflake guide explains how it works.
- Time Travel and recovery. You can query or restore past versions of data for up to 1 day on Standard Edition and up to 90 days on Enterprise and above.
- Open formats without leaving. Apache Iceberg tables let you keep data in open files while still using Snowflake.
- AI inside the platform. Cortex is Snowflake's family of built-in AI services. Cortex AI Functions (SQL functions such as AI_COMPLETE, AI_CLASSIFY and AI_FILTER) run large language models inside Snowflake's service perimeter. Snowflake CoWork (formerly Snowflake Intelligence) became generally available on 4 November 2025 and lets business users ask questions in plain language.
To be fair, rivals have their own strengths, such as Delta Lake time travel and Unity Catalog on Databricks. The real difference is how the whole platform fits your cloud, team and budget.
On scale, Snowflake reported product revenue of $1.49 billion for Q2 of fiscal 2027 (the quarter ended 31 July 2026), up 37% year on year, with 828 customers spending more than $1 million a year, 829 Forbes Global 2000 customers and more than 14,500 customers overall (Snowflake investor release, September 2026). Snowflake is listed on the NYSE as SNOW.
14. How to choose between Snowflake and its competitors
Short answer: Start from your cloud, your team's skills and your workload shape, then run a small proof of concept on real data before you decide.
This seven-step checklist works for a data team choosing a platform and for a learner choosing what to study.
- Which cloud do you use? All-in on AWS points to a look at Redshift as well as Snowflake. Google Cloud points to BigQuery. Microsoft and Power BI point to Fabric. More than one cloud points strongly to Snowflake or Databricks.
- Which language does your team think in? SQL-first analysts and ETL developers settle into Snowflake, BigQuery or Fabric quickly. Python and Spark teams often prefer Databricks.
- What does the workload look like? Steady BI reporting, spiky ad hoc queries, real-time dashboards and ML training each favour different billing models.
- Where must the data live? Check India regions and data-residency rules. Snowflake offers AWS Mumbai and Azure Central India; BigQuery lists Mumbai and Delhi.
- Do you need sharing with partners? If you share data with customers or partners often, Snowflake's Secure Data Sharing and Marketplace are a strong point.
- How open must the data be? If several engines must read the same tables, plan around Apache Iceberg or Delta Lake from day one.
- Run a two-week proof of concept. Load a real sample, run your top 20 queries, and compare cost, speed and effort. Then decide.
A quick "if this, then look at that" table:
For a view of the tools that sit around Snowflake rather than compete with it, such as dbt, Airflow, Fivetran and Power BI, see our Snowflake tools guide.
15. Companies that are not like-for-like Snowflake rivals
Short answer: Names such as AWS, Palantir and MongoDB often appear in "Snowflake competitors" searches, but they overlap with Snowflake only in parts.
- AWS, Microsoft and Google: they compete with Snowflake through Redshift, Fabric and BigQuery, but they are also the clouds Snowflake runs on. They are competitors and partners at the same time.
- Palantir: it is often grouped with Snowflake in stock market discussions about data and AI. But it is not usually bought as a general-purpose cloud warehouse in the way Redshift or BigQuery are, so the overlap is partial. We did not review Palantir's product pages, so we do not compare features.
- MongoDB: it is mainly known as a database for applications rather than a warehouse for analytics. Some teams load MongoDB data into Snowflake for reporting. Treat this as general context; we did not review MongoDB's product pages.
The rule of thumb: a real Snowflake competitor is a platform you could run your analytics warehouse or lakehouse on instead of Snowflake.
16. What Snowflake's competitors mean for your career
Short answer: Snowflake shows steady demand in India, and the core skills (SQL, modelling, dbt, one cloud) carry over to every competitor, so learning one platform well never locks you in.
Start with demand. On 25 October 2026, a Naukri search for "snowflake" returned about 25,910 results across India, including about 8,463 in Bengaluru, 4,969 in Hyderabad, 3,780 in Pune and 3,120 in Chennai (Naukri, October 2026). LinkedIn showed 6,000+ results for "Snowflake" in India on the same day. These are keyword-match counts with duplicates and overlapping cities, so read them as a demand signal, not open jobs. We do not compare them with "databricks" or "redshift" counts, because Naukri matches those keywords differently.
What the job descriptions say is more useful. We read 14 Snowflake job descriptions on 25 October 2026:
- SQL appeared in all 14. It is the skill that transfers to every platform in this post.
- dbt appeared in 9 of 14. dbt (data build tool) lets you write data transformations as version-controlled SQL models. It is a separate tool, so the skill is not tied to one platform. A Naukri search for "dbt snowflake" returned about 1,729 results on 25 October 2026.
- Python appeared in 9 of 14, and PySpark and Snowpark appeared in a few.
- AWS or Azure was asked in most, and Infosys listed Azure Data Factory in its key skills.
- Migration experience shows up at senior levels. The Deloitte Snowflake Architect listing asked for migration from Teradata, Redshift and SQL Server.
- Entry listings mention several platforms together. A Yotta Techports "Associate Data Forward Deployed Engineer" listing in Hyderabad (0 to 3 years) named "Snowflake, Databricks or BigQuery" as good to have.
On pay, AmbitionBox showed a typical range of ₹10.1 to 11.1 lakh a year for Snowflake Data Engineers in India (2 to 9 years, 1.3k salaries) and ₹8.2 to 9 lakh for Snowflake Developers (2 to 6 years, 4.2k salaries) in October 2026. Its Databricks Data Engineer page showed ₹10.6 to 11.7 lakh, but from only 54 salaries, a small sample. These ranges come from different job titles and employer mixes, so do not read them as "one platform pays more". For a Hyderabad view, see our Snowflake jobs in Hyderabad guide.
Which platform should you learn first? Here is a simple guide by background:
Our honest advice: go deep on one platform, build two or three real projects, and then learn enough about a second platform to talk about trade-offs in interviews. If an interviewer asks "Why Snowflake and not Databricks?", a clear answer shows you understand the market, not just one tool.
17. How Brolly Academy helps
Short answer: Brolly Academy's 45-day Snowflake course builds the SQL, loading, sharing and performance skills that transfer across every platform in this post.
If Snowflake is your first platform, our Snowflake Training in Hyderabad course is described as beginner-friendly, with SQL taught from scratch, for fresh graduates, IT professionals and non-IT career switchers. Here is what the course page lists (October 2026):
- Duration: 45 days, in classroom, live online or a self-paced video plan.
- Fees: Video ₹8,999, Online ₹17,999 and Classroom ₹22,999, with EMI available.
- Trainer: Mr. Bala Krishna, with 13+ years in data warehousing, SQL and Snowflake.
- Syllabus: 15 modules, from architecture and data warehousing concepts to stages, COPY INTO, Snowpipe, JSON, tasks and streams, secure data sharing, cloning, Time Travel, caching and performance, and pricing and resource monitoring.
- Projects: 6 projects, including a sales dashboard, an ETL pipeline, real-time data sharing and a Customer 360 view.
- Certificate: a Brolly Academy course completion certificate. The course prepares you for SnowPro exams such as SnowPro Core, but those exams are run by Snowflake and their fees are separate.
If your career plan includes a competitor platform too, Brolly also runs a separate Databricks course and a Microsoft Fabric course. The Snowflake course itself does not teach Databricks or Fabric.
Not sure whether Snowflake, Databricks or Fabric fits your background?
Book a free demo class with Brolly Academy in Hyderabad or online. Bring your current role and skills, and we will help you decide which platform to learn first, show you how the 45-day Snowflake course works, and explain how SQL, dbt and cloud skills carry across to its competitors.
Frequently asked questions
Who are Snowflake's biggest competitors?
Snowflake's biggest competitors are Databricks, Amazon Redshift, Google BigQuery and Microsoft Fabric. Databricks competes as a lakehouse platform for data engineering and AI, while Redshift, BigQuery and Fabric are the cloud providers' own warehouses on AWS, Google Cloud and Azure. Oracle Autonomous AI Database, Teradata Cloud, ClickHouse Cloud, Firebolt and open lakehouse stacks built on Apache Iceberg also compete for parts of Snowflake's work.
What is the best alternative to Snowflake?
There is no single best alternative; it depends on your cloud and your team. Databricks suits Python, Spark and machine learning teams. Redshift suits companies committed to AWS, BigQuery suits Google Cloud users, and Microsoft Fabric suits Power BI and SQL Server shops. ClickHouse and Firebolt suit very fast dashboards. Run a short proof of concept on your own data before choosing.
Is Databricks a competitor of Snowflake?
Yes, Databricks is Snowflake's closest competitor. Databricks sells the Databricks Data + AI Platform, a lakehouse that uses Delta Lake as its default table format and Unity Catalog for governance. It is strongest with Python, Spark and machine learning teams, while Snowflake is often preferred by SQL-first analytics teams. Some companies use both platforms side by side.
Is BigQuery better than Snowflake?
Neither is better in every case. BigQuery is serverless and charges either per TiB of data scanned or per slot-hour, which suits Google Cloud users with spiky queries. Snowflake charges for the time a virtual warehouse runs, in credits, and runs on AWS, Azure and Google Cloud. Compare both on your own workload rather than trusting vendor claims.
Is Microsoft Fabric a Snowflake competitor?
Yes. Microsoft Fabric Data Warehouse is a T-SQL lake warehouse that stores data as Delta tables in OneLake, with separate storage and compute. It competes with Snowflake mainly in companies that already use Power BI, SQL Server and Microsoft 365. Snowflake also runs on Azure, including the Azure Central India region in Pune, so Azure customers can choose either.
Is Azure Synapse still a Snowflake competitor?
Azure Synapse Analytics was Microsoft's earlier warehouse, and Microsoft now offers a path from it into Microsoft Fabric. Fabric's Migration Assistant moves workloads from Azure Synapse Analytics, SQL Server and Teradata into Fabric Data Warehouse. So when people compare Snowflake with Synapse today, the current Microsoft product to compare against is usually Fabric.
Does AWS compete with Snowflake?
Yes and no. AWS competes with Snowflake through Amazon Redshift, its own cloud warehouse with provisioned clusters and a Serverless option. But Snowflake also runs on AWS, including the AWS Mumbai region, so AWS is a partner too. A company can choose Snowflake for analytics and still run the rest of its systems on AWS.
Is Oracle a competitor to Snowflake?
Yes, mainly inside companies that already run Oracle. Oracle's documentation calls its service Autonomous AI Database, a fully managed, self-governing database for transactions, AI and analytics. Many large enterprises have older Oracle warehouses, and when they modernise, some stay with Oracle's cloud while others move to a platform such as Snowflake. Oracle and PL/SQL skills help on both kinds of project.
What is Teradata Cloud?
Teradata Cloud is how Teradata now presents its VantageCloud offer: a managed cloud version of its Autonomous Knowledge Platform with always-on and on-demand elastic compute, running on AWS, Azure and Google Cloud. Pricing is by quote. It matters for Snowflake careers because migrations from Teradata to Snowflake appear in senior job descriptions.
Is ClickHouse a Snowflake alternative?
ClickHouse Cloud is an alternative for specific workloads, mainly real-time dashboards, logs and event analytics where very fast answers matter. It bills per compute-unit-hour, metered per minute, and idle compute scales to zero with no monthly minimum. For broad enterprise warehousing with governance and data sharing, a team can keep Snowflake as the main warehouse and add a fast engine for one heavy workload.
Is there an open-source alternative to Snowflake?
Yes, there are open options. Firebolt's pricing page says it is fully open source and can be self-hosted. You can also build an open lakehouse with Apache Iceberg tables in your own cloud storage, queried by engines such as Spark, Flink or Trino. Snowflake itself supports Iceberg tables, so open formats and Snowflake can work together.
What is cheaper than Snowflake?
No platform is cheaper for every workload, and we found no independent benchmark we could verify. Each vendor bills in a different unit: Snowflake credits, Databricks DBUs, Redshift RPU-hours, BigQuery scanned TiB or slot-hours, Fabric capacity units, and compute-unit-hours on ClickHouse. The only fair test is to run your own queries on each platform for a few weeks and compare the bill.
How does Snowflake pricing compare with its competitors?
Snowflake bills compute in Platform Credits per second after a 60-second minimum, AI in AI Credits, and storage per TB per month. Its October 2026 table lists $2 to $6 per credit by edition and $23 per TB-month in AWS US East on demand. Prices vary by region and edition, and competitors use different units, so compare total monthly cost.
Are Palantir and Snowflake competitors?
Only partly. Palantir is often grouped with Snowflake in stock market discussions about data and AI, but it is not usually bought as a general-purpose cloud warehouse in the way Redshift or BigQuery are. A true Snowflake competitor is a platform you could run your analytics warehouse or lakehouse on instead, such as Databricks, Redshift, BigQuery or Fabric.
Are MongoDB and Snowflake competitors?
Not directly. MongoDB is mainly known as a database for applications, while Snowflake is a cloud platform for analytics, data engineering and AI. Many teams actually use them together, loading application data from MongoDB into Snowflake for reporting. The closer Snowflake rivals are Databricks, Redshift, BigQuery and Microsoft Fabric.
What makes Snowflake different from its competitors?
Snowflake separates storage, compute and cloud services, so independent virtual warehouses do not slow each other down. It runs on AWS, Azure and Google Cloud, shares live data with other accounts without copying it, offers Time Travel of up to 90 days on Enterprise Edition, supports Apache Iceberg tables and runs Cortex AI Functions inside its service perimeter.
Which Snowflake competitors have India regions?
Snowflake lists two India regions: AWS Mumbai and Azure Central India in Pune, with no Google Cloud India region. Google lists Mumbai and Delhi as BigQuery regions. For other platforms, check each vendor's region list for your account, because the pricing pages we checked did not show India prices and we do not quote Mumbai-specific prices.
What is a lakehouse, and how is it different from Snowflake?
A lakehouse combines a data lake, which is cheap files in cloud storage, with warehouse features such as transactions and governance. Databricks is the best-known lakehouse platform. Snowflake started as a managed cloud warehouse but now supports lakehouse patterns through Apache Iceberg tables, so the line between the two has become much thinner.
Is Snowflake a leader in the Gartner Magic Quadrant?
We could not verify Snowflake's position in the 2025 Gartner Magic Quadrant for Cloud Database Management Systems, so we do not state it. Databricks and Google each say on their own pages that they were named Leaders in 2025. Gartner does not endorse any vendor, so treat these reports as one input, not a final verdict.
Should I learn Snowflake or Databricks first?
If you come from SQL, ETL or database work, learn Snowflake first, because your SQL skills carry straight over. If you already write Python and Spark, Databricks may feel more natural. Either way, add dbt and one cloud, build real projects, and then learn enough of the second platform to discuss trade-offs in interviews.
Do Snowflake skills transfer to other platforms?
Yes, most of them do. In 14 Snowflake job descriptions we read in October 2026, SQL appeared in all 14, and dbt and Python each appeared in 9. Those skills, plus data modelling and cloud basics, are not tied to one platform, so they help on Databricks, BigQuery, Redshift and Fabric projects too. Platform-specific features still need fresh study.
Is there demand for Snowflake jobs in India?
Yes. On 25 October 2026, a Naukri search for "snowflake" returned about 25,910 results across India, with about 8,463 in Bengaluru and 4,969 in Hyderabad, and LinkedIn showed 6,000+ results. These are keyword-match counts with duplicates, not open jobs, but they show steady demand, led by Bengaluru and Hyderabad.
Will Snowflake be replaced by its competitors?
Nothing in the facts we checked suggests that. Snowflake reported product revenue of $1.49 billion for the quarter ended 31 July 2026, up 37% year on year, and more than 14,500 customers. Competition is real, especially from Databricks and the cloud providers, but open formats like Iceberg mean many companies now run Snowflake alongside other platforms.
Does Brolly Academy's Snowflake course cover competitors like Databricks?
No, the Brolly Academy Snowflake course focuses on Snowflake across 15 modules and 6 projects over 45 days, and it does not teach Databricks or Microsoft Fabric. Brolly runs separate Databricks and Microsoft Fabric courses for learners who want a second platform. The Snowflake course builds SQL, loading, sharing and performance skills that transfer widely.
How much does the Brolly Academy Snowflake course cost?
The Brolly Academy Snowflake course page lists three options in October 2026: a Video plan at ₹8,999, Online live classes at ₹17,999 and Classroom training in Hyderabad at ₹22,999, with EMI available. All run for 45 days. SnowPro exam fees are separate, because Snowflake runs and charges for those exams itself.
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