DBMS > Oracle NoSQL vs. TigerGraph vs. XTDB

System Properties Comparison Oracle NoSQL vs. TigerGraph vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Primary database model

Document store
Key-value store
Relational DBMS

Graph DBMS

Document store

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

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

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

www.tigergraph.com

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

Technical documentation

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

docs.tigergraph.com

www.xtdb.com/docs

Developer

Oracle

Juxt Ltd.

Initial release

2011

2017

2019

Current release

23.3, December 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

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

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

Linux
Solaris SPARC/x86

Linux

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

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

optional

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

SQL-like DML and DDL statements

SQL-like query language (GSQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

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

C++
Java

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Access rights for users and roles

Role-based access control

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More resources

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