DBMS > GigaSpaces vs. Informix vs. LeanXcale vs. OrigoDB vs. SQLite

System Properties Comparison GigaSpaces vs. Informix vs. LeanXcale vs. OrigoDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Key-value store
Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.gigaspaces.com

www.ibm.com/products/informix

www.leanxcale.com

origodb.com

www.sqlite.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

origodb.com/docs

www.sqlite.org/docs.html

Developer

Gigaspaces Technologies

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

LeanXcale

Robert Friberg et al

Dwayne Richard Hipp

Initial release

2000

1984

2015

2009

under the name LiveDB

2000

Current release

15.5, September 2020

14.10.FC5, November 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

free developer edition available

commercial

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++, .Net

C, C++ and Java

Server operating systems

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

User defined using .NET types and collections

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.

XML can be used for describing objects metadata

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

through Apache Derby

yes

SQL-92 is not fully supported

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C++
Java
Python
Scala

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

C
Java
Scala

.Net

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

Triggers

yes, event driven architecture

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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

Role-based access control

Users with fine-grained authentication, authorization, and auditing controls

Role based authorization

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