DBMS > Badger vs. RocksDB vs. Tkrzw vs. Transbase

System Properties Comparison Badger vs. RocksDB vs. Tkrzw vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

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

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/dgraph-io/badger

rocksdb.org

dbmx.net/tkrzw

www.transaction.de/en/products/transbase.html

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/facebook/rocksdb/wiki

www.transaction.de/en/products/transbase/features.html

Developer

DGraph Labs

Facebook, Inc.

Mikio Hirabayashi

Transaction Software GmbH

Initial release

2017

2013

2020

1987

Current release

9.2.1, May 2024

0.9.3, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache Version 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Java API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.