Alternatives to StarRocks

Exasol

Exasol SaaS is described for organizations needing multi-departmental analytics, in-database machine learning or AI, and complex data integration or virtualization.

Druid suits teams building user-facing analytics or working with streaming data, low-latency queries and ad hoc exploration.

Apache Hive

Hive suits teams managing large datasets with SQL across cloud storage, or connecting metadata and query clients such as Spark and Impala.

Kylin suits teams running SQL analytics on Linux that need high concurrency, streaming and batch analysis, or BI tool connections.

PrestoDB suits users who need to query data across heterogeneous sources and can deploy and manage a self-hosted engine.

Amazon Redshift

It suits teams running SQL analytics, dashboards, application workloads, data sharing, or ETL in the cloud.

It suits teams running SQL analytics and business intelligence on Hadoop-compatible storage and open table formats.

Apache Pinot

Apache Pinot suits teams building real-time analytics or user-facing applications with streaming and batch data.

Greenplum suits teams building large analytical warehouses or business intelligence systems, including analytics, machine learning, and AI workloads.

DuckDB UI

DuckDB UI suits DuckDB users who want to explore local data through a browser-based SQL notebook and table tools.

Teradata Cloud is aimed at large enterprises, including organizations in financial services, healthcare, life sciences, manufacturing, telecommunications, and transportation.

Firebolt

Firebolt suits engineers building analytical workloads who want Postgres-compatible SQL and a choice of self-managed or managed deployment.

QuestDB

QuestDB suits teams building time-series workloads that need SQL querying and low-latency ingestion.

MonetDB

MonetDB suits teams doing data warehousing, bulk processing, business intelligence, or scientific analysis who can self-host a database.

Yellowbrick is aimed at enterprises with demanding analytics workloads or data residency and security requirements.

Trino suits data teams querying and joining large datasets across multiple systems for analytics or data warehousing.