DBMS > Kyligence Enterprise vs. RocksDB vs. Ultipa

System Properties Comparison Kyligence Enterprise vs. RocksDB vs. Ultipa

Please select another system to include it in the comparison.

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)

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Key-value store

Graph DBMS

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	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

kyligence.io/kyligence-enterprise

rocksdb.org

www.ultipa.com

Technical documentation

github.com/facebook/rocksdb/wiki

www.ultipa.com/document

Developer

Kyligence, Inc.

Facebook, Inc.

Ultipa

Initial release

2016

2013

2019

Current release

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

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

C++

Server operating systems

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

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

RESTful HTTP API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.