DBMS > GeoSpock vs. Google Cloud Firestore vs. Microsoft SQL Server vs. SAP HANA vs. TerminusDB

System Properties Comparison GeoSpock vs. Google Cloud Firestore vs. Microsoft SQL Server vs. SAP HANA vs. TerminusDB

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
RDF store

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

geospock.com

firebase.google.com/products/firestore

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

www.sap.com/products/hana.html

terminusdb.com

Technical documentation

firebase.google.com/docs/firestore

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

help.sap.com/hana

terminusdb.github.io/terminusdb/#

Developer

GeoSpock

Google

Microsoft

SAP

DataChemist Ltd.

Initial release

2017

1989

2010

2018

Current release

2.0, September 2019

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

hosted

Linux
Windows

Appliance or cloud-service

Linux

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

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

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

SQLScript, R

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

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

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

yes

Role-based access control

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