DBMS > Datomic vs. DuckDB vs. Ehcache vs. RocksDB

System Properties Comparison Datomic vs. DuckDB vs. Ehcache vs. RocksDB

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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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A widely adopted Java cache with tiered storage options

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store

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

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	4.68
Rank	#76	Overall
	#41	Relational DBMS

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

Technical documentation

docs.datomic.com

duckdb.org/docs

www.ehcache.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Terracotta Inc, owned by Software AG

Facebook, Inc.

Initial release

2012

2018

2009

2013

Current release

1.0.6735, June 2023

0.10, February 2024

3.10.0, March 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

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

C++

Java

C++

Server operating systems

All OS with a Java VM

server-less

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

APIs and other access methods

RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JCache

C++ API
Java API

Supported programming languages

Clojure
Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

by using Terracotta Server

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

by using Terracotta Server

yes

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

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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

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