9 Best OLAP and Columnar Databases of 2026

1. 1

   ClickHouse Cloud

   The managed service for ClickHouse, an open source columnar database built for real-time analytics on large tables.

   9.1overall

   The managed service for ClickHouse, an open source columnar database built for real-time analytics on large tables.

   Best forData teams that need sub-second aggregations over billions of rows and want usage-based managed pricing.

   Adoption data

   3,000ClickHouse said in January 2026 that more than 3,000 customers use ClickHouse Cloud, with ARR growing more than 250 percent year over year.

   ClickHouse, ClickHouse raises $400M Series D, acquires Langfuse, launches Postgres (2026): “The company now serves more than 3,000 customers on its fully managed service, ClickHouse Cloud, with ARR growing more than 250 percent year over year.”

   ClickHouse is a columnar database designed for one job: answering aggregate queries over very large tables quickly, which is why it shows up behind product analytics, observability and ad-tech dashboards. ClickHouse Cloud runs the same engine as a managed service. Pricing is metered: in AWS us-east-1, Basic compute costs $0.2181 per unit-hour, Scale $0.2985, and storage is $25.30 per TB per month, with unused services scaled down to zero. Basic is capped at 1 TB of storage and is meant for starter projects, Scale adds compute-compute separation and two or more availability zones, and Enterprise adds SAML single sign-on and private regions. New accounts get $300 in credits for 30 days, and the open source distribution remains free for teams that prefer to self-host. ClickHouse reported more than 3,000 cloud customers in January 2026 and ARR growth above 250 percent. The trade-off is forecasting: bills depend on compute hours, so set autoscaling limits early.

   Strengths

   • +Lowest published entry compute rate among the managed services here
   • +Idle services stop billing for compute
   • +Same engine available as free open source if you outgrow the cloud budget

   Limitations

   • −Hourly compute plus storage makes monthly bills harder to forecast
   • −Basic tier limits storage and memory
   • −SSO and private regions require the Enterprise tier

   SummaryClickHouse Cloud is the best default columnar engine for fast analytics on large tables. Set autoscaling limits before production traffic arrives.

2. 2

   Google BigQuery

   Google Cloud's serverless columnar data warehouse, billed per TiB scanned or per slot-hour.

   8.8overall

   Google Cloud's serverless columnar data warehouse, billed per TiB scanned or per slot-hour.

   Best forTeams on Google Cloud that want OLAP queries with nothing to provision and a free monthly tier.

   Adoption data

   $30.7 billionAlphabet reported Google Cloud revenue of $30.7 billion in the third quarter of 2026, up 103 percent; it does not report BigQuery revenue separately.

   Alphabet, Alphabet Announces Third Quarter 2026 Results (Form 8-K, Exhibit 99.1) (2026): “Google Cloud delivered record growth as revenues increased 103% to $30.7 billion”

   BigQuery is the easiest columnar engine to start with because there is no cluster or warehouse to size. On the on-demand model, queries cost $6.25 per TiB scanned after a free first TiB each month, and the first 10 GiB of active logical storage are also free. When scan bills grow, teams can move to capacity pricing and buy slots by the hour in Standard, Enterprise or Enterprise Plus editions. BigQuery ML runs model training and prediction in SQL, and the Storage Read API includes 300 TiB of free reads a month for engines such as Spark. Google does not publish BigQuery revenue or customer counts, so adoption here rests on Google Cloud as a whole, which grew revenue 103 percent to $30.7 billion in the third quarter of 2026, and we score adoption below Snowflake for that reason. The main risk for OLAP work is cost from careless scans; partitioning and clustering large tables keeps the bytes scanned, and the bill, under control.

   Strengths

   • +Nothing to size or provision on the on-demand model
   • +Permanent free monthly query and storage tier
   • +Switch to slot capacity when scan costs grow

   Limitations

   • −Unpartitioned scans of large tables can get expensive
   • −No product-level revenue or customer count disclosed
   • −Fits best when data already sits in Google Cloud

   SummaryBigQuery is the best serverless OLAP start, especially on Google Cloud. Partition and cluster big tables from day one to keep scan costs down.

3. 3

   Snowflake

   A fully managed cloud data warehouse with columnar storage, billed per credit for compute.

   8.8overall

   A fully managed cloud data warehouse with columnar storage, billed per credit for compute.

   Best forData teams that want a governed, general-purpose analytical warehouse with elastic compute.

   Adoption data

   $1.49 billionSnowflake reported product revenue of $1.49 billion for its fiscal second quarter ended July 31, 2026, up 37 percent year over year.

   Snowflake, Snowflake Reports Financial Results for the Second Quarter of Fiscal 2027 (Form 8-K, Exhibit 99.1) (2026): “Product revenue of $1.49 billion in the second quarter, representing 37% year-over-year growth”

   Snowflake is the most widely bought standalone analytical warehouse, and for many teams it is the first columnar system they use. Its filings show product revenue of $1.49 billion in the quarter ended July 31, 2026, up 37 percent, which is the largest product-level figure in this list. Compute is billed per credit: $2.00 on Standard, $3.00 on Enterprise and $4.00 on Business Critical in AWS US East, with on-demand storage at $23 per TB per month. Enterprise adds 90-day data recovery and extra compute for busy periods, and Business Critical adds customer-managed keys and HIPAA, PCI DSS and FedRAMP support. Live data sharing lets accounts query each other's tables without copy pipelines. For OLAP work Snowflake is strongest on broad SQL, governance and mixed BI workloads; teams building sub-second dashboards for thousands of concurrent end users usually look at the real-time engines lower in this list. Model credit consumption per workload before committing.

   Strengths

   • +Largest disclosed product revenue among the vendors in this list
   • +Per-credit list prices published by edition and region
   • +Compute warehouses can be sized and suspended per workload

   Limitations

   • −Built for warehouse workloads rather than millisecond user-facing queries
   • −Credit burn depends on warehouse size and run time
   • −No permanent free plan

   SummarySnowflake is the safest choice for a governed general-purpose analytical warehouse. Pick a real-time engine instead if the goal is millisecond queries in a product.

4. 4

   DuckDB

   A free, in-process analytical SQL database that reads Parquet, CSV and Iceberg files directly.

   8.6overall

   A free, in-process analytical SQL database that reads Parquet, CSV and Iceberg files directly.

   Best forAnalysts and engineers who run OLAP queries on one machine or inside an application.

   Adoption data

   5.7%In the 2026 Stack Overflow Developer Survey, 5.7 percent of respondents to the database question had done extensive work in DuckDB over the past year.

   Stack Overflow, Databases, Technology data 2026, Stack Overflow Developer Survey (2026): “DuckDB 690 5.7%”

   DuckDB brings columnar OLAP to a laptop, a notebook or a server process without any cluster to run. It is an analytical SQL engine that lives inside the host application and reads and writes CSV, JSON, Parquet and Iceberg files, locally or in object storage, so many teams use it to query exports and data lake files directly. Its SQL dialect is inspired by PostgreSQL, extensions add formats and functions, and clients cover Python, Go, Java, Node.js, Rust and ODBC. The project also maintains DuckLake, a lakehouse format that keeps its catalog in a SQL database. The FAQ states DuckDB is fully open source under the MIT license, so the price is zero. In the 2026 Stack Overflow survey, 5.7 percent of database respondents had worked extensively with it. Its limit is scope: it is a single-node engine, not a shared service for many concurrent users.

   Strengths

   • +Free under MIT with no paid edition
   • +Queries Parquet files in place without loading them
   • +Used extensively by 5.7% of 2026 Stack Overflow database respondents

   Limitations

   • −Single-node engine, not a shared multi-user cluster
   • −No vendor support contract from the project itself
   • −Teams need another service for concurrent dashboard traffic

   SummaryDuckDB is the best free OLAP engine for single-machine analysis and embedded analytics. Pair it with a shared service when many users need the same data at once.

5. 5

   Amazon Redshift

   AWS's columnar data warehouse, offered as provisioned clusters or Redshift Serverless.

   8.4overall

   AWS's columnar data warehouse, offered as provisioned clusters or Redshift Serverless.

   Best forAWS-native data teams that want OLAP inside the same account, network and IAM setup.

   Adoption data

   $46.0 billionAmazon reported AWS segment sales of $46.0 billion in the third quarter of 2026, up 39 percent; it does not report Redshift revenue separately.

   Amazon, Amazon.com Announces Third Quarter Results (2026): “AWS segment sales increased 39% year-over-year to $46.0 billion.”

   Redshift is the columnar warehouse most AWS-based teams evaluate first, because it sits inside the account, VPC and IAM policies they already run. AWS lists provisioned clusters from $0.543 per hour and Redshift Serverless from $1.50 per hour. Serverless measures capacity in Redshift Processing Units, adjustable from 4 to 1024 RPUs and billed per second with a 60-second minimum, and it includes concurrency scaling and Spectrum queries on data in S3. Provisioned RG and RA3 nodes pair compute with managed storage that grows on its own. First-time Serverless users get a $300 credit valid for 90 days, and Redshift ML trains models through SageMaker from SQL. Amazon does not publish Redshift revenue or customer counts, so adoption reflects AWS as a whole, which grew segment sales 39 percent to $46.0 billion in the third quarter of 2026. The trade-off is the number of choices: node types, Serverless base capacity and reservations all change the bill.

   Strengths

   • +Runs in the same AWS account, VPC and IAM policies as the rest of the stack
   • +Choice of provisioned or serverless billing
   • +Queries S3 data in place through Spectrum

   Limitations

   • −Node families and serverless sizing add setup decisions
   • −No product-level revenue or customer count disclosed
   • −Less suited to workloads outside AWS

   SummaryRedshift is the natural OLAP warehouse for teams already committed to AWS. Start on Serverless to learn the workload, then price provisioned nodes for steady loads.

6. 6

   StarRocks

   An open source, MPP analytical database with a vectorized engine, now a Linux Foundation project.

   8.3overall

   An open source, MPP analytical database with a vectorized engine, now a Linux Foundation project.

   Best forEngineering teams that want free, self-hosted sub-second OLAP with joins and direct data lake queries.

   StarRocks is an open source analytical database aimed at the same sub-second dashboard workloads as ClickHouse, Pinot and Druid, with a stronger focus on joins. Its project documentation lists a native vectorized SQL engine, a cost-based optimizer, ANSI SQL with full TPC-H and TPC-DS support and compatibility with the MySQL protocol, so existing BI tools can connect. A primary key table model supports upserts and deletes while queries run, and materialized views refresh during loads and are picked automatically at query time. StarRocks can also query Apache Hive, Iceberg, Delta Lake and Hudi tables in place, and version 3.0 added a shared-data architecture that separates storage from compute. It is licensed under Apache 2.0 and governed as a Linux Foundation project, so the software costs nothing. The commercial company behind it, formerly CelerData, now sells managed and self-managed editions as PhoenixAI with quote-based pricing. We found no citable usage figure, so adoption is scored conservatively.

   Strengths

   • +Free under Apache 2.0
   • +Handles multi-table joins without denormalizing data first
   • +Shared-data architecture since version 3.0 separates storage from compute

   Limitations

   • −No published per-unit price for the managed service
   • −No citable customer or usage figure from the project
   • −Self-hosting means running frontend and backend nodes yourself

   SummaryStarRocks is the best free engine for sub-second OLAP that needs real joins and data lake access. Budget engineering time to run it or ask PhoenixAI for a managed quote.

7. 7

   SingleStore Helios

   A managed distributed SQL database that combines transactions and columnar analytics in one engine.

   8.1overall

   A managed distributed SQL database that combines transactions and columnar analytics in one engine.

   Best forTeams that need fast analytics on data that is also being written by an application.

   Adoption data

   $123 millionSingleStore reported ARR of more than $123 million at the end of its fiscal second quarter of 2026, up 23 percent, and a customer base of more than 400.

   SingleStore, SingleStore Delivers Record Performance in the Second Quarter of Fiscal Year 2026 (2025): “ARR of over $123 million at the end of Q2, growing 23% year-on-year”

   SingleStore takes a different route from the pure OLAP engines: one distributed SQL database that handles application writes and analytical reads together, so dashboards can query data seconds after an app stores it. Helios, the managed service, runs on AWS, Azure and Google Cloud. The pricing page lists one free shared workspace for development, Standard from $0.99 per hour with read replicas, database branching and a 99.9 or 99.99 percent SLA, and Enterprise from $1.49 per hour adding online point-in-time recovery, audit logging and customer-managed keys. New Standard users get $500 of free credits. Universal Storage covers relational, JSON, time-series, full-text, vector and geospatial data, the database speaks the MySQL wire protocol, and streaming pipelines load data continuously. SingleStore reported ARR above $123 million, up 23 percent, and a customer base of more than 400 in its fiscal second quarter of 2026. The adoption figure predates its private equity buyout and is smaller than the leaders here.

   Strengths

   • +Free shared workspace for development
   • +Transactions and analytics in the same database
   • +Hosted on AWS, Azure and Google Cloud

   Limitations

   • −Smaller disclosed customer base than the leaders
   • −Recovery and audit features sit in the Enterprise tier
   • −Credit-based bills need the calculator to estimate

   SummarySingleStore suits teams that want one database for operational writes and fast analytics. Pure OLAP teams with append-only data will find cheaper per-unit options above.

8. 8

   StarTree Cloud

   A managed service built on Apache Pinot for real-time, user-facing analytics.

   7.9overall

   A managed service built on Apache Pinot for real-time, user-facing analytics.

   Best forProduct teams serving analytics to many end users at once with fresh streaming data.

   Adoption data

   1 billionStarTree said in January 2026 that StarTree Cloud had reached 1 billion average daily queries.

   StarTree, StarTree Cloud Reaches 1 Billion Average Daily Queries (2026): “StarTree Cloud Reaches 1 Billion Average Daily Queries”

   StarTree sells Apache Pinot as a managed service. Pinot is an open source distributed OLAP database originally built at LinkedIn for analytics shown directly to end users, and the project describes P90 latencies in the tens of milliseconds and hundreds of thousands of concurrent queries per second. It ingests from Kafka, Pulsar and Kinesis in real time, supports upserts, and offers pluggable indexes including inverted, range, JSON, text and geospatial. StarTree publishes simple list prices per production vCPU: $0.21 per hour on its fully managed SaaS, which includes infrastructure, ingest and storage, and $0.11 per hour for Bring Your Own Cloud, where your provider bills the infrastructure. A Bring Your Own Kubernetes option covers air-gapped deployments on quote. StarTree reported that its cloud passed 1 billion average daily queries in January 2026. That is a usage signal rather than a customer count, so adoption is scored below vendors with filed revenue. Expect to spend time choosing indexes per query pattern.

   Strengths

   • +Designed for very high query concurrency on fresh data
   • +Simple per-vCPU list pricing with ingest and storage included on SaaS
   • +BYOC keeps data inside your own cloud account

   Limitations

   • −Usage figure is query volume, not a customer count
   • −No free plan on the pricing page
   • −Index choices need tuning for each query pattern

   SummaryStarTree is a strong pick for user-facing analytics with heavy concurrency on streaming data. Teams with mostly internal BI queries will get more from a general warehouse.

9. 9

   Imply Polaris

   A fully managed, cloud-native Apache Druid service for real-time analytics.

   7.5overall

   A fully managed, cloud-native Apache Druid service for real-time analytics.

   Best forTeams that want Apache Druid's streaming OLAP without running Druid clusters.

   Imply is the company founded around Apache Druid, and Polaris is its fully managed Druid service. Druid is an open source real-time analytics database that the project says runs OLAP queries in milliseconds on high-cardinality data sets with billions to trillions of rows, ingests from Kafka and Kinesis on arrival, and stores data in columnar, time-indexed, bitmap-indexed form. Polaris removes the cluster work: ingestion autoscales, high availability is included, and monitoring and alerts are built in. Pricing is published. Starter projects begin at $100 per month for up to 25 GB with variable performance, Standard begins at $600 per month for projects up to 9.6 TB with a 99.9 percent uptime SLA, and Custom is quoted. Ingestion is charged per GB, from $0.35 per GB for the first terabyte a month in AWS N. Virginia, and projects can be paused. Imply does not publish a current customer count we could cite, so adoption is scored conservatively. Model ingest volume carefully before choosing a project size.

   Strengths

   • +Clear monthly entry prices by project size
   • +Druid is built for high-cardinality, time-based data
   • +Pausing projects stops most project charges

   Limitations

   • −Starter is limited to 25 GB with variable performance
   • −Ingestion is billed per GB on top of project hours
   • −No citable customer count, so adoption is scored conservatively

   SummaryImply Polaris is the simplest way to run Druid for streaming, time-based analytics. Check ingest volume first, since it is billed separately from project hours.

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