DBMS > GeoSpock vs. Google Cloud Bigtable vs. H2GIS vs. JSqlDb vs. SWC-DB

System Properties Comparison GeoSpock vs. Google Cloud Bigtable vs. H2GIS vs. JSqlDb vs. SWC-DB

Editorial information provided by DB-Engines

Name

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

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Spatial extension of H2

JavaScript Query Language Database, stores JavaScript objects and primitives

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Spatial DBMS

Document store
Object oriented DBMS

Wide column store

Secondary database models

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

geospock.com

cloud.google.com/bigtable

www.h2gis.org

jsqldb.org (offline)

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cloud.google.com/bigtable/docs

www.h2gis.org/docs/home

Developer

GeoSpock

Google

CNRS

Konrad von Backstrom

Alex Kashirin

Initial release

2015

2013

2018

2020

Current release

2.0, September 2019

0.8, December 2018

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

GPL V3

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

Java

C++

Server operating systems

hosted

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

yes

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)

yes

SQL-like query language

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Proprietary protocol
Thrift

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java

JavaScript

C++

Server-side scripts

Stored procedures

yes

based on H2

functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

based on H2

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

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

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

Big data processing techniques to streamline analytics
5 October 2018, TechTarget

GeoSpock showcases rapid expansion with data insights
16 July 2018, Cambridge Independent

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page