Apache Cassandra vs Google Cloud Bigtable

Apache Cassandra is a free, open-source NoSQL distributed database for mission-critical data and large active datasets. Its masterless architecture gives each node the same functionality. The project says read and write throughput can grow linearly as machines are added, without downtime or application interruption. Cassandra can run on premises, with one cloud provider, across multiple providers, or in a combination of those environments. It supports replication across data centers and configurable consistency levels for queries, along with CQL, transactions, and horizontal scaling. The project lists audit logging for DML, DDL, and DCL activity, and fqltool for recording and replaying production workloads. Drivers are available for Java, Go, Python, and Node.js; downloads include tarballs and packages, and installation guidance covers Debian and RPM. The ecosystem includes tools and connectors for Apache Kafka, Apache Flink, Apache Spark, and Kubernetes. The project identifies version 5.0 as the latest GA release and says it is maintained until the 8.0 release. Cassandra is self-managed, and listed third-party ecosystem projects are not supported by its community.

Google Cloud Bigtable is a managed, low-latency NoSQL database for machine learning, operational analytics, and user-facing applications. It stores structured, semi-structured, and unstructured data in key-value and wide-column formats. SQL querying includes an API with more than 200 functions and support for aggregations, windowing, geospatial and JSON processing, and vector search. Compute scales horizontally, and instances can span up to eight regions with automatic replication between clusters. Google says multi-region instances offer 99.999% availability and protection against a regional failure. Integrations listed include Apache Spark, Hadoop, GKE, Dataflow, Dataproc, Vertex AI Vector Search, BigQuery, and LangChain. Bigtable provides Apache HBase and Cassandra APIs, plus migration tools for HBase, Cassandra, DynamoDB, and Aerospike. Security controls include IAM, customer-managed encryption keys, audit logging, and table-, column-, or row-level access control. Deployment is cloud-based. Google describes its capacity-based low-latency compute as more favorable for larger workloads than small applications. A 10-day trial is available subject to eligibility requirements.