DBMS > Apache Kylin vs. Blazegraph vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. MySQL

System Properties Comparison Apache Kylin vs. Blazegraph vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. MySQL

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Distributed Event Store optimized for Internet of Things use cases

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

Widely used open source RDBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

kylin.apache.org

blazegraph.com

www.ibm.com/products/db2-event-store

azure.microsoft.com/services/synapse-analytics

www.mysql.com

Technical documentation

kylin.apache.org/docs

wiki.blazegraph.com

www.ibm.com/docs/en/db2-event-store

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

Developer

Apache Software Foundation, originally contributed from eBay Inc

Blazegraph

IBM

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2015

2006

2017

2016

1995

Current release

3.1.0, July 2020

2.1.5, March 2019

2.0

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

commercial

free developer edition available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SPARQL is used as query language

yes

through the embedded Spark runtime

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
Java
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Transact SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

yes

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

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

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

fine grained access rights according to SQL-standard

yes

Users with fine-grained authorization concept

no user groups or roles

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