DBMS > Ehcache vs. GigaSpaces vs. Oracle vs. Sqrrl

System Properties Comparison Ehcache vs. GigaSpaces vs. Oracle vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A widely adopted Java cache with tiered storage options

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

Widely used RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Website

www.ehcache.org

www.gigaspaces.com

www.oracle.com/database

sqrrl.com

Technical documentation

www.ehcache.org/documentation

docs.gigaspaces.com/latest/landing.html

docs.oracle.com/en/database

Developer

Terracotta Inc, owned by Software AG

Gigaspaces Technologies

Oracle

Amazon

originally Sqrrl Data, Inc.

Initial release

2009

2000

1980

2012

Current release

3.10.0, March 2022

15.5, September 2020

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2; Commercial licenses available

commercial

restricted free version is available

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

C and C++

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

with proprietary extensions

APIs and other access methods

JCache

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Java

.Net
C++
Java
Python
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Cache Event Listeners

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Sharding, horizontal partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

isolation level can be parameterized

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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