DBMS > KeyDB vs. Manticore Search vs. Oracle vs. Stardog

System Properties Comparison KeyDB vs. Manticore Search vs. Oracle vs. Stardog

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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

Multi-storage database for search, including full-text search.

Widely used RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

github.com/Snapchat/KeyDB
keydb.dev

manticoresearch.com

www.oracle.com/database

www.stardog.com

Technical documentation

docs.keydb.dev

manual.manticoresearch.com

docs.oracle.com/en/database

docs.stardog.com

Developer

EQ Alpha Technology Ltd.

Manticore Software

Oracle

Stardog-Union

Initial release

2019

2017

1980

2010

Current release

6.0, February 2023

23c, September 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

BSD-3

Open Source

GPL version 2

commercial

restricted free version is available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

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

Linux
macOS
Windows

Data scheme

schema-free

Fixed schema

yes

Schemaless in JSON and XML columns

schema-free and OWL/RDFS-schema support

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

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Import/export of XML data possible

Secondary indexes

yes

by using the Redis Search module

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

PL/SQL

also stored procedures in Java possible

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

isolation level can be parameterized

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

The original contents of fields are not stored in the Manticore index.

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'

yes

User concepts

Access control

simple password-based access control and ACL

fine grained access rights according to SQL-standard

Access rights for users and roles

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