DBMS > KeyDB vs. Oracle Coherence vs. Sadas Engine

System Properties Comparison KeyDB vs. Oracle Coherence vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Key-value store

Relational DBMS

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

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

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

www.oracle.com/java/coherence

www.sadasengine.com

Technical documentation

docs.keydb.dev

docs.oracle.com/en/middleware/standalone/coherence

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

EQ Alpha Technology Ltd.

Oracle

SADAS s.r.l.

Initial release

2019

2007

2006

Current release

14.1, August 2023

8.0

License

Commercial or Open Source

Open Source

BSD-3

commercial

free trial version available

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

C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

JCache
JPA
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

.Net
C++
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

configurable

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

optionally

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

simple password-based access control and ACL

authentification to access the cache via certificates or http basic authentication

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

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