DBMS > DolphinDB vs. Kinetica vs. Sadas Engine

System Properties Comparison DolphinDB vs. Kinetica vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Fully vectorized database across both GPUs and CPUs

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	2.20
Rank	#109	Overall
	#8	Time Series DBMS
	#9	Vector DBMS

Score	0.47
Rank	#248	Overall
	#116	Relational DBMS

Score	0.00
Rank	#382	Overall
	#155	Relational DBMS

Website

www.dolphindb.com

www.kinetica.com

www.sadasengine.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.kinetica.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

DolphinDB, Inc

Kinetica

SADAS s.r.l.

Initial release

2018

2012

2006

Current release

v2.00.4, January 2022

7.1, August 2021

8.0

License

Commercial or Open Source

commercial

free community version available

commercial

free trial version available

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.

Implementation language

C++

C, C++

C++

Server operating systems

Linux
Windows

Linux

AIX
Linux
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C++
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

GPU vRAM or System RAM

yes

managed by 'Learn by Usage'

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles on table level

Access rights for users, groups and roles according to SQL-standard

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More resources

Recent citations in the news

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks and Files

How GPUs Are Helping Paris’ Public Hospital System Combat the Spread of COVID-19
15 October 2020, NVIDIA Blog

Kinetica rolls machine learning libraries into its GPU-powered database
24 January 2017, SiliconANGLE

GPU Database Market Size, Share & Trends Report, 2030
29 July 2024, Grand View Research

Kinetica Adds $6 Million in Acceleration Funding and Expands Management Team
26 September 2016, Business Wire

provided by Google News

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