DBMS > Elasticsearch vs. GridGain vs. KairosDB

System Properties Comparison Elasticsearch vs. GridGain vs. KairosDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

GridGain is an in-memory computing platform, built on Apache Ignite

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Search engine

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Website

www.elastic.co/elasticsearch

www.gridgain.com

github.com/kairosdb/kairosdb

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.gridgain.com/docs/index.html

kairosdb.github.io

Developer

Elastic

GridGain Systems, Inc.

Initial release

2010

2007

2013

Current release

8.6, January 2023

GridGain 8.5.1

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache 2.0

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

Java, C++, .Net

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

Java API
RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by using the 'percolation' feature

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

Memcached and Redis integration

yes

User concepts

Access control

Security Hooks for custom implementations

simple password-based access control

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

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