DBMS > GBase vs. JaguarDB vs. Microsoft SQL Server vs. Sqrrl vs. Teradata

System Properties Comparison GBase vs. JaguarDB vs. Microsoft SQL Server vs. Sqrrl vs. Teradata

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

Adaptable, secure NoSQL built on Apache Accumulo

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column 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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.gbase.cn

www.jaguardb.com

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

sqrrl.com

www.teradata.com

Technical documentation

www.jaguardb.com/support.html

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

docs.teradata.com

Developer

General Data Technology Co., Ltd.

DataJaguar, Inc.

Microsoft

Amazon

originally Sqrrl Data, Inc.

Teradata

Initial release

2004

2015

1989

2012

1984

Current release

GBase 8a, GBase 8s, GBase 8c

3.3 July 2023

SQL Server 2022, November 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C, Java, Python

C++

the server part. Clients available in other languages

C++

Java

Server operating systems

Linux

Linux
Windows

Linux

hosted
Linux

Data scheme

yes

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

Standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

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

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

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

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

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

Server-side scripts

Stored procedures

user defined functions

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

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

Sharding

making use of Hadoop

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes, but depending on the SQL-Server Edition

selectable replication factor

making use of Hadoop

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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

yes

rights management via user accounts

fine grained access rights according to SQL-standard

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

fine grained access rights according to SQL-standard

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