DBMS > Blazegraph vs. Microsoft SQL Server vs. Splice Machine vs. Teradata

System Properties Comparison Blazegraph vs. Microsoft SQL Server vs. Splice Machine vs. Teradata

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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

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

Microsofts flagship relational DBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

blazegraph.com

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

splicemachine.com

www.teradata.com

Technical documentation

wiki.blazegraph.com

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

splicemachine.com/how-it-works

docs.teradata.com

Developer

Blazegraph

Microsoft

Splice Machine

Teradata

Initial release

2006

1989

2014

1984

Current release

2.1.5, March 2019

SQL Server 2022, November 2022

3.1, March 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SPARQL is used as query language

yes

SQL 2016 + extensions

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

JDBC
Native Spark Datasource
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

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

yes

Java

yes

UDFs, stored procedures, table functions in parallel

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

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)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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