DBMS > Kinetica vs. Oracle Rdb vs. Sadas Engine vs. SiriDB vs. Transwarp Hippo

System Properties Comparison Kinetica vs. Oracle Rdb vs. Sadas Engine vs. SiriDB vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

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

Open Source Time Series DBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Time Series DBMS

Vector DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

www.kinetica.com

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

siridb.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.kinetica.com

www.oracle.com/database/technologies/related/rdb-doc.html

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

docs.siridb.com

Developer

Kinetica

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Cesbit

Initial release

2012

1984

2006

2017

2023

Current release

7.1, August 2021

7.4.1.1, 2021

8.0

1.0, May 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

commercial

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++

Server operating systems

Linux

HP Open VMS

AIX
Linux
Windows

Linux

Linux
macOS

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

Numeric data

Vector, Numeric and String

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 DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

HTTP API

RESTful HTTP API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

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

C++
Java
Python

Server-side scripts

Stored procedures

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

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

yes, on a single node

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'

yes

User concepts

Access control

Access rights for users and roles on table level

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

simple rights management via user accounts

Role based access control and fine grained access rights

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

Oracle Adds New AI-Enabling Features To MySQL HeatWave
23 March 2023, Forbes

Should we all consolidate databases for the storage benefits? Reg vultures deploy DevOps, zoos, haircuts
18 September 2020, The Register

2013 Data Science Salary Survey – O'Reilly
4 May 2013, O'Reilly Media

provided by Google News

Share this page