DBMS > EXASOL vs. Firebase Realtime Database vs. GigaSpaces vs. Splice Machine vs. SQLite

System Properties Comparison EXASOL vs. Firebase Realtime Database vs. GigaSpaces vs. Splice Machine vs. SQLite

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.exasol.com

firebase.google.com/products/realtime-database

www.gigaspaces.com

splicemachine.com

www.sqlite.org

Technical documentation

www.exasol.com/resources

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

splicemachine.com/how-it-works

www.sqlite.org/docs.html

Developer

Exasol

Google

acquired by Google 2014

Gigaspaces Technologies

Splice Machine

Dwayne Richard Hipp

Initial release

2000

2012

2000

2014

2000

Current release

15.5, September 2020

3.1, March 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

AGPL 3.0, commercial license available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Java

Server operating systems

hosted

Linux
macOS
Solaris
Windows

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

SQL-92 is not fully supported

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

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

JDBC
Native Spark Datasource
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
Lua
Python
R

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

C#
C++
Java
JavaScript (Node.js)
Python
R
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

user defined functions

limited functionality with using 'rules'

yes

Java

Triggers

yes

Callbacks are triggered when data changes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Map-Reduce pattern can be built with XAP task executors

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

yes, based on authentication and database rules

Role-based access control

Access rights for users, groups and roles according to SQL-standard

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