DBMS > etcd vs. EXASOL vs. Hazelcast vs. MySQL vs. Solr

System Properties Comparison etcd vs. EXASOL vs. Hazelcast vs. MySQL vs. Solr

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A widely adopted in-memory data grid

Widely used open source RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key/Value like access via memcached API

Search engine

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Spatial DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

etcd.io
github.com/etcd-io/etcd

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.exasol.com/resources

hazelcast.org/imdg/docs

dev.mysql.com/doc

solr.apache.org/resources.html

Developer

Exasol

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2000

2008

1995

2006

Current release

3.4, August 2019

5.3.6, November 2023

8.4.0, April 2024

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C and C++

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

gRPC
JSON over HTTP

.Net
JDBC
ODBC
WebSocket

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java
Lua
Python
R

.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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

yes

proprietary syntax

Java plugins

Triggers

yes, watching key changes

yes

Events

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Replicated Map

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

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

ACID

not for MyISAM storage engine

optimistic locking

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

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