DBMS > Google Cloud Bigtable vs. Hypertable vs. Kingbase vs. RocksDB vs. TerminusDB

System Properties Comparison Google Cloud Bigtable vs. Hypertable vs. Kingbase vs. RocksDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

An open source BigTable implementation based on distributed file systems such as Hadoop

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store
Wide column store

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cloud.google.com/bigtable

www.kingbase.com.cn

rocksdb.org

terminusdb.com

Technical documentation

cloud.google.com/bigtable/docs

github.com/facebook/rocksdb/wiki

terminusdb.github.io/terminusdb/#

Developer

Google

Hypertable Inc.

BeiJing KINGBASE Information technologies inc.

Facebook, Inc.

DataChemist Ltd.

Initial release

2015

2009

1999

2013

2018

Current release

0.9.8.11, March 2016

V8.0, August 2021

9.2.1, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and Java

C++

Prolog, Rust

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language (WOQL)

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

C++ API
Thrift

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor on file system level

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Role-based access control

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