DBMS > Datomic vs. Lovefield vs. Manticore Search vs. MySQL vs. SiteWhere

System Properties Comparison Datomic vs. Lovefield vs. Manticore Search vs. MySQL vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

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.

Widely used open source RDBMS

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

www.datomic.com

google.github.io/lovefield

manticoresearch.com

www.mysql.com

github.com/sitewhere/sitewhere

Technical documentation

docs.datomic.com

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

manual.manticoresearch.com

dev.mysql.com/doc

sitewhere1.sitewhere.io/index.html

Developer

Cognitect

Google

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

SiteWhere

Initial release

2012

2014

2017

1995

2010

Current release

1.0.6735, June 2023

2.1.12, February 2017

6.0, February 2023

8.3.0, January 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

JavaScript

C++

C and C++

Java

Server operating systems

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

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

predefined scheme

Typing

predefined data types such as float or date

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.

Can index from XML

yes

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

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

Supported programming languages

Clojure
Java

JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

yes

proprietary syntax

Triggers

By using transaction functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

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