DBMS > RocksDB vs. StarRocks vs. Tkrzw

System Properties Comparison RocksDB vs. StarRocks vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

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

Primary database model

Key-value store

Relational DBMS

Key-value store

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

rocksdb.org

www.starrocks.io

dbmx.net/tkrzw

Technical documentation

github.com/facebook/rocksdb/wiki

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Facebook, Inc.

The Linux Foundation

since Feb 2023

Mikio Hirabayashi

Initial release

2013

2020

Current release

8.11.4, April 2024

2.5.3, March 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

C++

Server operating systems

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

JDBC
MySQL protocol

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

Role based access control and fine grained access rights

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