DBMS > Graph Engine vs. Oracle NoSQL vs. SAP HANA vs. XTDB

System Properties Comparison Graph Engine vs. Oracle NoSQL vs. SAP HANA vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Graph DBMS
Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.graphengine.io

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

www.sap.com/products/hana.html

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

Technical documentation

www.graphengine.io/docs/manual

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

help.sap.com/hana

www.xtdb.com/docs

Developer

Microsoft

Oracle

SAP

Juxt Ltd.

Initial release

2010

2011

2010

2019

Current release

24.1, May 2024

2.0 SPS07 (April 4, 2023), April 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT License

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

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

Java

Clojure

Server operating systems

.NET

Linux
Solaris SPARC/x86

Appliance or cloud-service

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

Data scheme

yes

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

yes

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

C#
C++
F#
Visual Basic

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

Clojure
Java

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

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

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

User concepts

Access control

Access rights for users and roles

yes

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.