DBMS > GBase vs. RocksDB vs. Transwarp StellarDB vs. VoltDB vs. Yaacomo

System Properties Comparison GBase vs. RocksDB vs. Transwarp StellarDB vs. VoltDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

A distributed graph DBMS built for enterprise-level graph applications

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

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

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.gbase.cn

rocksdb.org

www.transwarp.cn/en/product/stellardb

www.voltdb.com

yaacomo.com

Technical documentation

github.com/facebook/rocksdb/wiki

docs.voltdb.com

Developer

General Data Technology Co., Ltd.

Facebook, Inc.

Transwarp

VoltDB Inc.

Q2WEB GmbH

Initial release

2004

2013

2010

2009

Current release

GBase 8a, GBase 8s, GBase 8c

9.2.1, May 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C, Java, Python

C++

Java, C++

Server operating systems

Linux

Linux
OS X

for development

Android
Linux
Windows

Data scheme

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

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

only a subset of SQL 99

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

C++ API
Java API

OpenCypher

Java API
JDBC
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

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

yes

FOREIGN KEY constraints are not supported

yes

Transaction concepts

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

ACID

yes

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

fine grained access rights according to SQL-standard

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