DBMS > GigaSpaces vs. KeyDB vs. OpenEdge vs. TimesTen

System Properties Comparison GigaSpaces vs. KeyDB vs. OpenEdge vs. TimesTen

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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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Application development environment with integrated database management system

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

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

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

www.gigaspaces.com

github.com/Snapchat/KeyDB
keydb.dev

www.progress.com/openedge

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

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.keydb.dev

documentation.progress.com/output/ua/OpenEdge_latest

docs.oracle.com/database/timesten-18.1

Developer

Gigaspaces Technologies

EQ Alpha Technology Ltd.

Progress Software Corporation

Oracle, TimesTen Performance Software, HP

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

Initial release

2000

2019

1984

1998

Current release

15.5, September 2020

OpenEdge 12.2, March 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD-3

commercial

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++

Server operating systems

Linux
macOS
Solaris
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

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

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

close to SQL 92

yes

APIs and other access methods

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

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C++
Java
Python
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Progress proprietary ABL (Advanced Business Language)

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Lua

yes

PL/SQL

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

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

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

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

Users and groups

fine grained access rights according to SQL-standard

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