DBMS > Riak KV vs. RocksDB vs. TDengine vs. TigerGraph

System Properties Comparison Riak KV vs. RocksDB vs. TDengine vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Distributed, fault tolerant key-value store

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

Time Series DBMS and big data platform

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Time Series DBMS

Graph DBMS

Secondary database models

Relational DBMS

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

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

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

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

rocksdb.org

github.com/taosdata/TDengine
tdengine.com

www.tigergraph.com

Technical documentation

www.tiot.jp/riak-docs/riak/kv/latest

github.com/facebook/rocksdb/wiki

docs.tdengine.com

docs.tigergraph.com

Developer

OpenSource, formerly Basho Technologies

Facebook, Inc.

TDEngine, previously Taos Data

Initial release

2009

2013

2019

2017

Current release

3.2.0, December 2022

8.11.4, April 2024

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

Open Source

AGPL V3, also commercial editions available

commercial

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

Erlang

C++

Server operating systems

Linux
OS X

Linux

Linux
Windows

Linux

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

restricted

SQL

Support of SQL

Standard SQL with extensions for time-series applications

SQL-like query language (GSQL)

APIs and other access methods

HTTP API
Native Erlang Interface

C++ API
Java API

JDBC
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

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

C++
Java

Server-side scripts

Stored procedures

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

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

User concepts

Access control

yes, using Riak Security

yes

Role-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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