DBMS > JSqlDb vs. Kinetica vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OrientDB

System Properties Comparison JSqlDb vs. Kinetica vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OrientDB

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

JavaScript Query Language Database, stores JavaScript objects and primitives

Fully vectorized database across both GPUs and CPUs

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Object oriented DBMS

Relational DBMS

Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Website

jsqldb.org (offline)

www.kinetica.com

azure.microsoft.com/en-us/services/storage/tables

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

orientdb.org

Technical documentation

docs.kinetica.com

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

www.orientdb.com/docs/last/index.html

Developer

Konrad von Backstrom

Kinetica

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

2018

2012

1989

2010

Current release

0.8, December 2018

7.1, August 2021

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Java

Server operating systems

Linux
macOS
Windows

Linux

hosted

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

SQL-like DML and DDL statements

yes

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C++
Java
JavaScript (Node.js)
Python

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

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

functions in JavaScript

user defined functions

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

Java, Javascript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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