DBMS > GeoSpock vs. Lovefield vs. Microsoft Azure Table Storage vs. RDF4J vs. SwayDB

System Properties Comparison GeoSpock vs. Lovefield vs. Microsoft Azure Table Storage vs. RDF4J vs. SwayDB

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

Embeddable relational database for web apps written in pure JavaScript

A Wide Column Store for rapid development using massive semi-structured datasets

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

geospock.com

google.github.io/lovefield

azure.microsoft.com/en-us/services/storage/tables

rdf4j.org

swaydb.simer.au

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

rdf4j.org/documentation

Developer

GeoSpock

Google

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Simer Plaha

Initial release

2014

2012

2004

2018

Current release

2.0, September 2019

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Javascript

JavaScript

Java

Scala

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

JavaScript

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

optimistic locking

ACID

Isolation support depends on the API used

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights based on private key authentication or shared access signatures

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More resources

Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

Inside Azure File Storage
7 October 2015, azure.microsoft.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

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13 June 2019, Markets Insider

provided by Google News

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