DBMS > Hazelcast vs. MySQL vs. Sphinx vs. SWC-DB vs. YDB

System Properties Comparison Hazelcast vs. MySQL vs. Sphinx vs. SWC-DB vs. YDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Widely used open source RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

A high performance, scalable Wide Column DBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Search engine

Wide column store

Document store
Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Time Series DBMS

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

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

hazelcast.com

www.mysql.com

sphinxsearch.com

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

hazelcast.org/imdg/docs

dev.mysql.com/doc

sphinxsearch.com/docs

ydb.tech/en/docs

Developer

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Alex Kashirin

Yandex

Initial release

2008

1995

2001

2020

2019

Current release

5.3.6, November 2023

8.4.0, April 2024

3.5.1, February 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, 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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

SQL-like query language

SQL-like query language (YQL)

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Proprietary protocol
Thrift

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

Go
Java
JavaScript (Node.js)
PHP
Python

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 with MySQL Cluster or MySQL Fabric

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication

none

Active-passive shard 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

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

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Access rights defined for Yandex Cloud users

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