DBMS > Datomic vs. InfinityDB vs. LevelDB vs. Memcached vs. MySQL

System Properties Comparison Datomic vs. InfinityDB vs. LevelDB vs. Memcached vs. MySQL

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

A Java embedded Key-Value Store which extends the Java Map interface

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

In-memory key-value store, originally intended for caching

Widely used open source RDBMS

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

www.datomic.com

boilerbay.com

github.com/google/leveldb

www.memcached.org

www.mysql.com

Technical documentation

docs.datomic.com

boilerbay.com/infinitydb/manual

github.com/google/leveldb/blob/main/doc/index.md

github.com/memcached/memcached/wiki

dev.mysql.com/doc

Developer

Cognitect

Boiler Bay Inc.

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2002

2011

2003

1995

Current release

1.0.7075, December 2023

4.0

1.23, February 2021

1.6.27, May 2024

8.4.0, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD

Open Source

BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

C++

C and C++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
Java

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

yes

proprietary syntax

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

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

yes

with automatic compression on writes

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

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept

no user groups or roles

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