DBMS > AnzoGraph DB vs. Microsoft SQL Server vs. Snowflake vs. SwayDB vs. Teradata

System Properties Comparison AnzoGraph DB vs. Microsoft SQL Server vs. Snowflake vs. SwayDB vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Microsofts flagship relational DBMS

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.snowflake.com

swaydb.simer.au

www.teradata.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

docs.snowflake.net/manuals/index.html

docs.teradata.com

Developer

Cambridge Semantics

Microsoft

Snowflake Computing Inc.

Simer Plaha

Teradata

Initial release

2018

1989

2014

2018

1984

Current release

2.3, January 2021

SQL Server 2022, November 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

restricted free version is available

commercial

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

Linux

Linux
Windows

hosted

hosted
Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

schema-free

yes

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

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

SQL 2016 + extensions

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

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

CLI Client
JDBC
ODBC

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

Supported programming languages

C++
Java
Python

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

JavaScript (Node.js)
Python

Java
Kotlin
Scala

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

Server-side scripts

Stored procedures

user defined functions and aggregates

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

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

yes

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes, but depending on the SQL-Server Edition

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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