DBMS > DataFS vs. Elasticsearch vs. Ignite vs. SQLite

System Properties Comparison DataFS vs. Elasticsearch vs. Ignite vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Widely used embeddable, in-process RDBMS

Primary database model

Object oriented DBMS

Search engine

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

newdatabase.com

www.elastic.co/elasticsearch

ignite.apache.org

www.sqlite.org

Technical documentation

dev.mobiland.com/Overview.xsp

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

apacheignite.readme.io/docs

www.sqlite.org/docs.html

Developer

Mobiland AG

Elastic

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2018

2010

2015

2000

Current release

1.1.263, October 2022

8.6, January 2023

Apache Ignite 2.6

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

Public Domain

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

C++, Java, .Net

Server operating systems

Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

server-less

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP/JSON API

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C#
C++
VB.Net

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

C#
C++
Java
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

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

Triggers

no, except callback-events from server when changes happened

yes

by using the 'percolation' feature

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

none

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

Immediate Consistency

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Windows-Profile

Security Hooks for custom implementations

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