DBMS > Apache Phoenix vs. Blazegraph vs. IBM Db2 Event Store vs. Microsoft SQL Server

System Properties Comparison Apache Phoenix vs. Blazegraph vs. IBM Db2 Event Store vs. Microsoft SQL Server

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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 scale-out RDBMS with evolutionary schema built on Apache HBase

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

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

phoenix.apache.org

blazegraph.com

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

www.microsoft.com/en-us/sql-server

Technical documentation

phoenix.apache.org

wiki.blazegraph.com

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

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

Blazegraph

IBM

Microsoft

Initial release

2014

2006

2017

1989

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

2.1.5, March 2019

2.0

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

commercial

free developer edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

SPARQL is used as query language

yes

through the embedded Spark runtime

yes

APIs and other access methods

JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Active-active shard replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

fine grained access rights according to SQL-standard

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