DBMS > Apache Kylin vs. GraphDB vs. Microsoft Azure Synapse Analytics vs. Snowflake

System Properties Comparison Apache Kylin vs. GraphDB vs. Microsoft Azure Synapse Analytics vs. Snowflake

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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

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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	1.20
Rank	#175	Overall
	#80	Relational DBMS

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

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

kylin.apache.org

www.ontotext.com

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

Technical documentation

kylin.apache.org/docs

graphdb.ontotext.com/documentation

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

Social network pages

Developer

Apache Software Foundation, originally contributed from eBay Inc

Ontotext

Microsoft

Snowflake Computing Inc.

Initial release

2015

2000

2016

2014

Current release

3.1.0, July 2020

10.4, October 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Cloud-based only

Only available as a cloud service

yes

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

All OS with a Java VM
Linux
OS X
Windows

hosted

Data scheme

yes

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

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

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

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

C#
Java
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

Transact SQL

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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.

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.

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

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

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