DBMS > Atos Standard Common Repository vs. Datomic vs. Lovefield vs. Manticore Search vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. Datomic vs. Lovefield vs. Manticore Search vs. SiteWhere

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable relational database for web apps written in pure JavaScript

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

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.datomic.com

google.github.io/lovefield

manticoresearch.com

github.com/sitewhere/sitewhere

Technical documentation

docs.datomic.com

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

manual.manticoresearch.com

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

Cognitect

Google

Manticore Software

SiteWhere

Initial release

2016

2012

2014

2017

2010

Current release

1703

1.0.6735, June 2023

2.1.12, February 2017

6.0, February 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Common Public Attribution License Version 1.0

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

Java, Clojure

JavaScript

C++

Java

Server operating systems

Linux

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Fixed schema

predefined scheme

Typing

predefined data types such as float or date

optional

yes

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

LDAP

RESTful HTTP API

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

HTTP REST

Supported programming languages

All languages with LDAP bindings

Clojure
Java

JavaScript

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

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Triggers

yes

By using transaction functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

But extensive use of caching in the application peers

none

Sharding

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

none

Synchronous replication based on Galera library

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

In-memory capabilities

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

yes

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

LDAP bind authentication

Users with fine-grained authorization concept

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