DBMS > Microsoft SQL Server vs. OpenEdge vs. SingleStore vs. TigerGraph

System Properties Comparison Microsoft SQL Server vs. OpenEdge vs. SingleStore vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Application development environment with integrated database management system

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	5.91
Rank	#61	Overall
	#34	Relational DBMS

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

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

www.progress.com/openedge

www.singlestore.com

www.tigergraph.com

Technical documentation

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

documentation.progress.com/output/ua/OpenEdge_latest

docs.singlestore.com

docs.tigergraph.com

Developer

Microsoft

Progress Software Corporation

SingleStore Inc.

Initial release

1989

1984

2013

2017

Current release

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

8.5, January 2024

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++

C++, Go

C++

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

64 bit version required

Linux

Data scheme

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

SQL

Support of SQL

yes

close to SQL 92

yes

but no triggers and foreign keys

SQL-like query language (GSQL)

APIs and other access methods

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

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

Progress proprietary ABL (Advanced Business Language)

Bash
C
C#
Java
JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

since Version 11.4

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

fine grained access rights according to SQL-standard

Users and groups

Fine grained access control via users, groups and roles

Role-based 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

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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