DBMS > Lovefield vs. Machbase Neo vs. Manticore Search vs. Oracle Coherence vs. RethinkDB

System Properties Comparison Lovefield vs. Machbase Neo vs. Manticore Search vs. Oracle Coherence vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

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

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

google.github.io/lovefield

machbase.com

manticoresearch.com

www.oracle.com/java/coherence

rethinkdb.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

manual.manticoresearch.com

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

rethinkdb.com/docs

Developer

Google

Machbase

Manticore Software

Oracle

The Linux Foundation

since July 2017

Initial release

2014

2013

2017

2007

2009

Current release

2.1.12, February 2017

V8.0, August 2023

6.0, February 2023

14.1, August 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

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

JavaScript

C++

Java

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

JCache
JPA
RESTful HTTP API

Supported programming languages

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Triggers

Using read-only observers

yes

Live Events

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

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

none

selectable replication factor

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

authentification to access the cache via certificates or http basic authentication

yes

users and table-level permissions

More information provided by the system vendor

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More resources

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