DBMS > etcd vs. GridDB vs. MySQL vs. Solr

System Properties Comparison etcd vs. GridDB vs. MySQL vs. Solr

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Scalable in-memory time series database optimized for IoT and Big Data

Widely used open source RDBMS

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

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Key-value store
Relational DBMS

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	2.09
Rank	#120	Overall
	#10	Time Series DBMS

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

griddb.net

www.mysql.com

solr.apache.org

Technical documentation

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

docs.griddb.net

dev.mysql.com/doc

solr.apache.org/resources.html

Developer

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2013

1995

2006

Current release

3.4, August 2019

5.1, August 2022

8.4.0, April 2024

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux

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

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

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON 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

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

yes

proprietary syntax

Java plugins

Triggers

yes, watching key changes

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.

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

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 within container, eventual consistency across containers

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 at container level

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 can be defined per database

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.