DBMS > GraphDB vs. Kinetica vs. Rockset vs. SAP HANA

System Properties Comparison GraphDB vs. Kinetica vs. Rockset vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Fully vectorized database across both GPUs and CPUs

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.10
Rank	#100	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.84
Rank	#209	Overall
	#35	Document stores

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

www.ontotext.com

www.kinetica.com

rockset.com

www.sap.com/products/hana.html

Technical documentation

graphdb.ontotext.com/documentation

docs.kinetica.com

docs.rockset.com

help.sap.com/hana

Social network pages

Developer

Ontotext

Kinetica

Rockset

SAP

Initial release

2000

2012

2019

2010

Current release

10.4, October 2023

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Cloud-based only

Only available as a cloud service

yes

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

Java

C, C++

C++

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux

hosted

Appliance or cloud-service

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL-like DML and DDL statements

Read-only SQL queries, including JOINs

yes

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

JDBC
ODBC
RESTful HTTP API

HTTP REST

JDBC
ODBC

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

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

GPU vRAM or System RAM

yes

User concepts

Access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Access rights for users and roles on table level

Access rights for users and organizations can be defined via Rockset console

yes

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

Using GraphDB’s Natural Language Interface to Talk with Your Content
29 March 2024

Choosing A Graph Data Model to Best Serve Your Use Case
27 March 2024

Event Extraction Based on Fine-Tuned Text2Event Transformer Speeds up the Fact-checking Process
22 March 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.