DBMS > Datomic vs. Ehcache vs. Firebolt vs. Lovefield

System Properties Comparison Datomic vs. Ehcache vs. Firebolt 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

A widely adopted Java cache with tiered storage options

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.datomic.com

www.ehcache.org

www.firebolt.io

google.github.io/lovefield

Technical documentation

docs.datomic.com

www.ehcache.org/documentation

docs.firebolt.io

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

Developer

Cognitect

Terracotta Inc, owned by Software AG

Firebolt Analytics Inc.

Google

Initial release

2012

2009

2020

2014

Current release

1.0.7075, December 2023

3.10.0, March 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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

hosted

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP API

JCache

.Net
ODBC
RESTful HTTP API

Supported programming languages

Clojure
Java

Java

Go
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

yes

Cache Event Listeners

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

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

by using Terracotta Server

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

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

using a tiered cache-storage approach

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

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