DBMS > Cachelot.io vs. Datomic vs. Lovefield vs. Oracle Berkeley DB vs. Stardog

System Properties Comparison Cachelot.io vs. Datomic vs. Lovefield vs. Oracle Berkeley DB vs. Stardog

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Widely used in-process key-value store

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
RDF store

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cachelot.io

www.datomic.com

google.github.io/lovefield

www.oracle.com/database/technologies/related/berkeleydb.html

www.stardog.com

Technical documentation

docs.datomic.com

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

docs.oracle.com/cd/E17076_05/html/index.html

docs.stardog.com

Developer

Cognitect

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Stardog-Union

Initial release

2015

2012

2014

1994

2010

Current release

1.0.7075, December 2023

2.1.12, February 2017

18.1.40, May 2020

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

limited edition free

Open Source

Apache 2.0

Open Source

commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++

Java, Clojure

JavaScript

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL interfaced based on SQLite is available

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Memcached protocol

RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

Clojure
Java

JavaScript

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

By using transaction functions

Using read-only observers

yes

only for the SQL API

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

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

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

Access rights for users and roles

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