DBMS > CrateDB vs. Manticore Search vs. Oracle Coherence vs. RethinkDB

System Properties Comparison CrateDB vs. Manticore Search vs. Oracle Coherence vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

Oracles in-memory data grid solution

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Search engine

Key-value store

Document store

Secondary database models

Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

cratedb.com

manticoresearch.com

www.oracle.com/java/coherence

rethinkdb.com

Technical documentation

cratedb.com/docs

manual.manticoresearch.com

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

rethinkdb.com/docs

Developer

Crate

Manticore Software

Oracle

The Linux Foundation

since July 2017

Initial release

2013

2017

2007

2009

Current release

5.8.1, August 2024

6.0, February 2023

14.1, August 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache Version 2

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++

Java

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, binary, float, bool, date, geometry

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

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

JCache
JPA
RESTful HTTP API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

.Net
C++
Java

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

Triggers

yes

Live Events

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Synchronous replication based on Galera library

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

yes

isolated transactions for atomic changes and binary logging for safe writes

configurable

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

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

yes

optionally

yes

In-memory capabilities

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

yes

User concepts

Access control

rights management via user accounts

authentification to access the cache via certificates or http basic authentication

yes

users and table-level permissions

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More resources

DB-Engines blog posts

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