DBMS > GeoSpock vs. Kinetica vs. SAP HANA vs. SiriDB

System Properties Comparison GeoSpock vs. Kinetica vs. SAP HANA vs. SiriDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Fully vectorized database across both GPUs and CPUs

In-memory, column based data store. Available as appliance or cloud service

Open Source Time Series DBMS

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

geospock.com

www.kinetica.com

www.sap.com/products/hana.html

siridb.com

Technical documentation

docs.kinetica.com

help.sap.com/hana

docs.siridb.com

Developer

GeoSpock

Kinetica

SAP

Cesbit

Initial release

2012

2010

2017

Current release

2.0, September 2019

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Javascript

C, C++

Server operating systems

hosted

Linux

Appliance or cloud-service

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

HTTP API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights for users and roles on table level

yes

simple rights management via user accounts

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