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

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

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Object oriented DBMS

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	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Website

jsqldb.org (offline)

www.kinetica.com

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

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

Technical documentation

docs.kinetica.com

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

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Konrad von Backstrom

Kinetica

Microsoft

Open Source, formerly Basho Technologies

Initial release

2018

2012

1989

2015

Current release

0.8, December 2018

7.1, August 2021

SQL Server 2022, November 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

C++

Erlang

Server operating systems

Linux
macOS
Windows

Linux

hosted

Linux
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

yes

schema-free

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

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

yes

yes, limited

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

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

HTTP API
Native Erlang Interface

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

functions in JavaScript

user defined functions

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

Erlang

Triggers

yes

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

yes

pre-commit hooks and post-commit 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

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

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.