DBMS > Apache Doris vs. Datomic vs. H2 vs. RocksDB vs. SwayDB

System Properties Comparison Apache Doris vs. Datomic vs. H2 vs. RocksDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

doris.apache.org
github.com/apache/doris

Technical documentation

github.com/apache/doris/wiki

docs.datomic.com

www.h2database.com/html/main.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from Baidu

Cognitect

Thomas Mueller

Facebook, Inc.

Simer Plaha

Initial release

2017

2012

2005

2013

2018

Current release

1.2.2, February 2023

1.0.6735, June 2023

2.2.220, July 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Clojure

Java

C++

Scala

Server operating systems

Linux

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

JDBC
MySQL client

RESTful HTTP API

JDBC
ODBC

C++ API
Java API

Supported programming languages

Java

Clojure
Java

Java

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

Java Stored Procedures and User-Defined Functions

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

But extensive use of caching in the application peers

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomic execution of operations

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

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

fine grained access rights according to SQL-standard

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