DBMS > Apache Kylin vs. GigaSpaces vs. JanusGraph vs. openGauss vs. RocksDB

System Properties Comparison Apache Kylin vs. GigaSpaces vs. JanusGraph vs. openGauss vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Relational DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

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

Website

kylin.apache.org

www.gigaspaces.com

janusgraph.org

gitee.com/opengauss
opengauss.org

rocksdb.org

Technical documentation

kylin.apache.org/docs

docs.gigaspaces.com/latest/landing.html

docs.janusgraph.org

docs.opengauss.org/en
gitee.com/opengauss/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from eBay Inc

Gigaspaces Technologies

Linux Foundation; originally developed as Titan by Aurelius

Huawei and openGauss community

Facebook, Inc.

Initial release

2015

2000

2017

2019

2013

Current release

3.1.0, July 2020

15.5, September 2020

0.6.3, February 2023

3.0, March 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

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

Java, C++, .Net

Java

C, C++, Java

C++

Server operating systems

Linux

Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-99 for query and DML statements

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C++
Java
Python
Scala

Clojure
Java
Python

C
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning (by range, list and hash)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Role-based access control

User authentification and security via Rexster Graph Server

Access rights for users, groups and roles according to SQL-standard

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