DBMS > GeoSpock vs. Microsoft SQL Server vs. ReductStore vs. Riak TS vs. SAP HANA

System Properties Comparison GeoSpock vs. Microsoft SQL Server vs. ReductStore vs. Riak TS vs. SAP HANA

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

Microsofts flagship relational DBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial 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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

geospock.com

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

github.com/reductstore
www.reduct.store

www.sap.com/products/hana.html

Technical documentation

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

www.reduct.store/docs

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

help.sap.com/hana

Developer

GeoSpock

Microsoft

ReductStore LLC

Open Source, formerly Basho Technologies

SAP

Initial release

1989

2023

2015

2010

Current release

2.0, September 2019

SQL Server 2022, November 2022

1.9, March 2024

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Business Source License 1.1

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

Java, Javascript

C++

C++, Rust

Erlang

Server operating systems

hosted

Linux
Windows

Docker
Linux
macOS
Windows

Linux
OS X

Appliance or cloud-service

Data scheme

yes

schema-free

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.

yes

Secondary indexes

temporal, categorical

yes

restricted

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

yes, limited

yes

APIs and other access methods

JDBC

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

HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

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

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

Erlang

SQLScript, R

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

yes

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