DBMS > Apache Pinot vs. GigaSpaces vs. SQLite vs. TimesTen

System Properties Comparison Apache Pinot vs. GigaSpaces vs. SQLite vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

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	0.58
Rank	#244	Overall
	#111	Relational DBMS

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

pinot.apache.org

www.gigaspaces.com

www.sqlite.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.pinot.apache.org

docs.gigaspaces.com/latest/landing.html

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation and contributors

Gigaspaces Technologies

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2015

2000

1998

Current release

1.0.0, September 2023

15.5, September 2020

3.45.3 (15 April 2024), April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

Server operating systems

All OS with a Java JDK11 or higher

Linux
macOS
Solaris
Windows

server-less

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python

.Net
C++
Java
Python
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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

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

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

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