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Baidu Tera vs Google Cloud Bigtable

Baidu Tera

github.com

Google Cloud Bigtable

cloud.google.com

Side by side

FigureBaidu TeraGoogle Cloud Bigtable
Price from—$0.03/mo
Free plan—Yes
Free trial—Yes
Open source——
Web—Yes
LinuxYes—
APIYesYes
Self-hostedYes—
Plans published010
Spec score · Wide-Column Databases7.2 (#11)7.8 (#6)
Data modelTera stores sparse, distributed, multidimensional tables indexed by row key, column key, and timestamp.It is a key-value and wide-column store for structured, semi-structured, and unstructured data.
IntegrationsTera's README lists HDFS and other filesystems, ZooKeeper and Nexus lock services, and Sofa-pbrpc as infrastructure dependencies.The product page lists integrations with Apache Spark, Hadoop, GKE, Dataflow, Dataproc, Vertex AI Vector Search, BigQuery, and LangChain.
ProductTera is a high-performance distributed NoSQL database designed for real-time applications.Bigtable is a fully managed, low-latency NoSQL database service for machine learning, operational analytics, and user-facing applications.

Plans

Baidu Tera

No plans published.

Baidu Tera pricing →

Google Cloud Bigtable

  • Enterprise$0.65 a month
  • Enterprise Plus$0.85 a month
  • Data BoostFree
  • HDD storage$0.03 a month
  • Standard backup storage$0.03 a month
  • Hot backup storage$0.12 a month
  • SSD storage$0.17 a month
  • In-memory tier$0.20 a month
  • Enterprise compute capacity$0.65 a month
  • Enterprise Plus compute capacity$0.85 a month

Google Cloud Bigtable pricing →

In their own words

Baidu Tera

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.

Visit github.com

Google Cloud Bigtable

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.

Visit cloud.google.com