DBMS > Datomic vs. HBase vs. Lovefield

System Properties Comparison Datomic vs. HBase vs. Lovefield

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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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Wide column store

Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

www.datomic.com

hbase.apache.org

google.github.io/lovefield

Technical documentation

docs.datomic.com

hbase.apache.org/book.html

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

Developer

Cognitect

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Google

Initial release

2012

2008

2014

Current release

1.0.6735, June 2023

2.3.4, January 2021

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2

Open Source

Apache 2.0

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, Clojure

Java

JavaScript

Server operating systems

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Supported programming languages

Clojure
Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Coprocessors in Java

Triggers

By using transaction functions

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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