DBMS > Blazegraph vs. InterSystems Caché vs. Microsoft SQL Server vs. SiteWhere vs. Spark SQL

System Properties Comparison Blazegraph vs. InterSystems Caché vs. Microsoft SQL Server vs. SiteWhere vs. Spark SQL

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.

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

Microsofts flagship relational DBMS

M2M integration platform for persisting/querying time series data

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
RDF store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

blazegraph.com

www.intersystems.com/products/cache

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

github.com/sitewhere/sitewhere

spark.apache.org/sql

Technical documentation

wiki.blazegraph.com

docs.intersystems.com

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

sitewhere1.sitewhere.io/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Blazegraph

InterSystems

Microsoft

SiteWhere

Apache Software Foundation

Initial release

2006

1997

1989

2010

2014

Current release

2.1.5, March 2019

2018.1.4, May 2020

SQL Server 2022, November 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

restricted free version is available

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

Scala

Server operating systems

Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

depending on used data model

yes

predefined scheme

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

SPARQL is used as query language

yes

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

HTTP REST

JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
C++
Java

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

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

none

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

Sharding

based on HBase

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

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

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

User concepts

Access control

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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