DBMS > Kyligence Enterprise vs. RocksDB vs. XTDB

System Properties Comparison Kyligence Enterprise vs. RocksDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, built on top of Apache Kylin

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

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

Primary database model

Relational DBMS

Key-value store

Document store

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

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

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

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

kyligence.io/kyligence-enterprise

rocksdb.org

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

Technical documentation

github.com/facebook/rocksdb/wiki

www.xtdb.com/docs

Developer

Kyligence, Inc.

Facebook, Inc.

Juxt Ltd.

Initial release

2016

2013

2019

Current release

9.2.1, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Clojure

Server operating systems

Linux

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

Data scheme

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

ANSI SQL for queries (using Apache Calcite)

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

HTTP REST
JDBC

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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