DBMS > JanusGraph vs. LeanXcale vs. Oracle NoSQL vs. YTsaurus

System Properties Comparison JanusGraph vs. LeanXcale vs. Oracle NoSQL vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Graph DBMS

Key-value store
Relational DBMS

Document store
Key-value store
Relational DBMS

Document store
Key-value store

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

janusgraph.org

www.leanxcale.com

www.oracle.com/database/nosql/technologies/nosql

ytsaurus.tech

Technical documentation

docs.janusgraph.org

docs.oracle.com/en/database/other-databases/nosql-database/index.html

ytsaurus.tech/docs/en

Developer

Linux Foundation; originally developed as Titan by Aurelius

LeanXcale

Oracle

Yandex

Initial release

2017

2015

2011

2023

Current release

0.6.3, February 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache License, Version 2.0

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
OS X
Unix
Windows

Linux
Solaris SPARC/x86

Ubuntu

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

through Apache Derby

SQL-like DML and DDL statements

YQL, an SQL-based language, is supported

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

Clojure
Java
Python

C
Java
Scala

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

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

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

off heap cache

User concepts

Access control

User authentification and security via Rexster Graph Server

Access rights for users and roles

Access Control Lists

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More resources

Recent citations in the news

Database Deep Dives: JanusGraph
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3 October 2019, The New Stack

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