DBMS > AnzoGraph DB vs. CockroachDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. Trino

System Properties Comparison AnzoGraph DB vs. CockroachDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. Trino

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.cockroachlabs.com

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

www.sap.com/products/technology-platform/sql-anywhere.html

trino.io

Technical documentation

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

www.cockroachlabs.com/docs

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

help.sap.com/docs/SAP_SQL_Anywhere

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Cambridge Semantics

Cockroach Labs

Microsoft

SAP

formerly Sybase

Trino Software Foundation

Initial release

2018

2015

1989

1992

2012

2020 rebranded from PrestoSQL

Current release

2.3, January 2021

24.1.0, May 2024

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0, commercial license available

commercial

restricted free version is available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C++

Java

Server operating systems

Linux

Linux
macOS
Windows

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

Schema-free and OWL/RDFS-schema support

dynamic schema

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

depending on connected data-source

SQL

Support of SQL

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

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

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

JDBC

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

ADO.NET
HTTP API
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C++
Java
Python

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
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

yes, in C/C++, Java, .Net or Perl

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

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

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

depending on connected data-source

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

depending on connected data-source

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

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

Role-based access control

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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