DBMS > Hazelcast vs. Percona Server for MySQL vs. RocksDB vs. Valentina Server vs. Vitess

System Properties Comparison Hazelcast vs. Percona Server for MySQL vs. RocksDB vs. Valentina Server vs. Vitess

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

Object-relational database and reports server

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.10
Rank	#119	Overall
	#57	Relational DBMS

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

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

hazelcast.com

www.percona.com/software/mysql-database/percona-server

rocksdb.org

www.valentina-db.net

vitess.io

Technical documentation

hazelcast.org/imdg/docs

www.percona.com/downloads/Percona-Server-LATEST

github.com/facebook/rocksdb/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

vitess.io/docs

Developer

Hazelcast

Percona

Facebook, Inc.

Paradigma Software

The Linux Foundation, PlanetScale

Initial release

2008

2013

1999

2013

Current release

5.3.6, November 2023

8.0.36-28, 2024

9.2.1, May 2024

5.7.5

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2

Open Source

BSD

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Java

C and C++

C++

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Docker
Linux
macOS

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

C++ API
Java API

ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

proprietary syntax

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication
XtraDB Cluster

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

yes

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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