DBMS > BigObject vs. Elasticsearch vs. GridGain

System Properties Comparison BigObject vs. Elasticsearch vs. GridGain

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Search engine

Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

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

Website

bigobject.io

www.elastic.co/elasticsearch

www.gridgain.com

Technical documentation

docs.bigobject.io

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

www.gridgain.com/docs/index.html

Developer

BigObject, Inc.

Elastic

GridGain Systems, Inc.

Initial release

2015

2010

2007

Current release

8.6, January 2023

GridGain 8.5.1

License

Commercial or Open Source

commercial

free community edition available

Open Source

Elastic License

commercial

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

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

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

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

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Lua

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes (replicated cache)

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

none

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Memcached and Redis integration

yes

User concepts

Access control

Security Hooks for custom implementations

More information provided by the system vendor

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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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24 January 2024, PR Newswire

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5 October 2023, Datanami

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8 February 2024, PR Newswire

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