DBMS > GridGain vs. JaguarDB vs. Microsoft SQL Server vs. mSQL vs. Qdrant

System Properties Comparison GridGain vs. JaguarDB vs. Microsoft SQL Server vs. mSQL vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

www.gridgain.com

www.jaguardb.com

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

hughestech.com.au/products/msql

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

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

qdrant.tech/documentation

Developer

GridGain Systems, Inc.

DataJaguar, Inc.

Microsoft

Hughes Technologies

Qdrant

Initial release

2007

2015

1989

1994

2021

Current release

GridGain 8.5.1

3.3 July 2023

SQL Server 2022, November 2022

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

Apache Version 2.0

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.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java, C++, .Net

C++

the server part. Clients available in other languages

C++

Rust

Server operating systems

Linux
OS X
Solaris
Windows

Linux

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC

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

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication

yes, but depending on the SQL-Server Edition

none

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Security Hooks for custom implementations

rights management via user accounts

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.