DBMS > RocksDB vs. Trafodion vs. XTDB

System Properties Comparison RocksDB vs. Trafodion vs. XTDB

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Transactional SQL-on-Hadoop DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Relational DBMS

Document store

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

rocksdb.org

trafodion.apache.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/facebook/rocksdb/wiki

trafodion.apache.org/documentation.html

www.xtdb.com/docs

Developer

Facebook, Inc.

Apache Software Foundation, originally developed by HP

Juxt Ltd.

Initial release

2013

2014

2019

Current release

8.11.4, April 2024

2.3.0, February 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

C++, Java

Clojure

Server operating systems

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

C++ API
Java API

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HBase

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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