Open-source Google Cloud Bigtable alternatives

ScyllaDB is a NoSQL database that implements the Apache Cassandra and Amazon DynamoDB APIs, so existing applications and drivers for those systems can talk to it. It is written in C++ on the Seastar framework and is aimed at real-time big data workloads that need high throughput and predictable latency.

The project describes a shared-nothing approach in which each CPU core manages its own slice of data, which it says increases throughput and storage capacity per machine and cuts hardware costs. Building the database is demanding: it needs a very recent C++23 compiler and many up-to-date libraries, so the project offers a frozen toolchain as a pre-configured Docker image that includes everything required. You then only need Docker or Podman to compile it.

The repository's license is listed as 'Other' on GitHub, so confirm the current terms before using it commercially. You can run ScyllaDB on your own servers or consume it as a managed cloud service from the company. It suits teams that have outgrown Cassandra's resource footprint or want a DynamoDB-compatible database they can run themselves.

Apache Cassandra is an open-source, transactional, distributed NoSQL database. It is built to manage very large amounts of data across many machines, aiming for linear scalability and proven fault tolerance whether it runs on commodity servers or in the cloud, with no loss of performance. It is written in Java and developed under the Apache Software Foundation.

The project site presents Cassandra 5.0 along with documentation, a quickstart and community resources, and recent talks from the community cover topics such as Storage Attached Indexes, the Accord transaction protocol, mutation tracking, backups with Medusa, a sidecar process and analytics integrations. Cassandra is queried through CQL and can be run in clusters spanning racks, data centers or cloud regions.

Cassandra is licensed under Apache-2.0 and you run it yourself, either on your own servers or on cloud virtual machines or Kubernetes. It is typically chosen for write-heavy, always-on applications such as time-series data, messaging, IoT and large user-facing systems that must stay available when individual nodes fail.

Apache HBase is an open-source database that is distributed, versioned and column-oriented, modeled on the Bigtable design described in a paper by Chang and colleagues at Google. Bigtable relies on the Google File System, and in the same way HBase delivers comparable capabilities on top of Apache Hadoop and its distributed file system.

It is intended for storing very large tables across a cluster, with rows indexed by key and columns grouped into families. The project documentation includes a Reference Guide with a quick start section, downloads on the project site, and mailing lists plus a Slack channel for discussion. The code is written in Java.

HBase is an Apache Software Foundation project under the Apache-2.0 license and is deployed on your own Hadoop-based clusters, though several cloud providers also bundle it in managed big data offerings. It suits data engineering teams that need low-latency random access to large datasets.