Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud.
Starting at $0.25 per hour
Best Greenplum Alternatives ranked by AI · updated Aug 2026
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Greenplum is a PostgreSQL-based massively parallel data warehouse for large-scale analytics. It is aimed at enterprises that need distributed SQL, mature workload management, and compatibility with established Greenplum deployments.
Top 6 Greenplum alternatives
ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real-time.
Snowflake is a cloud data platform for storing, processing, sharing, and analyzing enterprise data. It serves data teams, analysts, and developers with...
Pros
- Broader cloud data warehouse ecosystem than 1010data
- Strong separation of storage and compute for flexible scaling
- Extensive data-sharing and governance capabilities
Cons
- Costs can be difficult to predict without workload controls
- Requires more tooling for advanced data preparation and machine learning
- Less specialized for 1010data's retail-focused analytical workflows
Usage-based; contact sales
StarRocks is an open-source, MPP analytical database built for real-time analytics and high-concurrency business intelligence. It combines fast vectorized execution with lakehouse...
Pros
- Very close feature and workload fit for Apache Doris deployments
- Strong performance for interactive dashboards and concurrent users
- Supports real-time ingestion and querying across warehouse and lake data
Cons
- Smaller community and third-party ecosystem than ClickHouse
- Requires specialized expertise for distributed deployment and tuning
- Some advanced capabilities depend on version or managed offering
Free and open source; managed cloud pricing varies
Apache Cloudberry is an open-source massively parallel processing database for large-scale analytics and data warehousing. It is designed for organizations that need...
Pros
- PostgreSQL-compatible SQL and tooling
- Columnar storage and parallel execution for analytical workloads
- Can run on self-managed infrastructure and public clouds
Cons
- Requires more operational expertise than fully managed warehouses
- Smaller ecosystem and community than Snowflake or BigQuery
- Not optimized for high-volume point lookups or transactional applications
Free and open source
6
Google BigQuery is a serverless, highly scalable, and cost-effective multi-cloud data warehouse designed for business agility.
Pros
- Serverless
- Scalable
- Integration with Google Cloud services
Cons
- Can be expensive for large datasets
- Limited support for complex queries
Pay-as-you-go pricing model
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