Apache HBase vs Baidu Tera

Apache HBase is a distributed data store for applications that need random, real-time reads and writes with strict consistency. It runs on Hadoop and HDFS, with automatic failover and sharding, and is designed to scale across commodity clusters. The project describes hosting tables with billions of rows and millions of columns. Clients can connect through a Java API or REST and Thrift gateways. Highlighted workloads include time-series and metrics, IoT telemetry, ad tech and personalization, message and audit logs, security analytics, and genomics and research. HBase is free and self-hosted, with Linux and API platforms listed; version 3.0.0 is listed as a release artifact. Operators must configure authentication and authorization because the default configuration does not enable them. Security guidance covers Kerberos, SASL, access control lists, visibility labels, and optional TLS, and recommends keeping services within a trusted network perimeter rather than exposing them to the public internet. Operating a distributed deployment requires systems, software, and networking skills.

Baidu Tera is a free, self-hosted distributed NoSQL database for real-time applications. It stores sparse, multidimensional tables indexed by row key, column key and timestamp, with the project describing scale to petabytes across thousands of commodity servers. Tera supports strict consistency, MVCC, automatic failover, online schema changes and snapshots. Configurable automatic sharding can use ranged or hashed strategies, with linear and modular scalability. Storage options include RAMDISK, SSD and disk tables, plus tiered and block caches and Bloom Filters for real-time queries. Applications can connect through C++, Java, Python and REST APIs. Its architecture includes an SDK, master and tablet servers using an enhanced LevelDB engine. Deployment can use raw machines or Docker, with pseudo-distributed operation on one host. The repository lists BSD-3-Clause and Apache-2.0 licenses.