DBMS > GeoSpock vs. LeanXcale vs. Transwarp ArgoDB

System Properties Comparison GeoSpock vs. LeanXcale vs. Transwarp ArgoDB

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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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Search engine

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

Score	0.25
Rank	#296	Overall
	#43	Key-value stores
	#133	Relational DBMS

Score	0.00
Rank	#385	Overall
	#157	Relational DBMS

Website

geospock.com

www.leanxcale.com

www.transwarp.cn/en/product/argodb

Technical documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

GeoSpock

LeanXcale

Transwarp

Initial release

2015

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

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

Server operating systems

hosted

Data scheme

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.

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

through Apache Derby

yes

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C
Java
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

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

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More resources

Recent citations in the news

GeoSpock and X-Locations Collaborate to Deliver Next Generation Location Data Analysis in Japan
25 March 2019, Business Wire

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, vanillaplus.com

GeoSpock Confirms Commitment to Japanese Market with New Office Opening in Tokyo, Japan
3 October 2019, Geospatial World

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

provided by Google News

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