DBMS > Blueflood vs. GeoMesa vs. GridDB vs. LokiJS

System Properties Comparison Blueflood vs. GeoMesa vs. GridDB vs. LokiJS

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Scalable in-memory time series database optimized for IoT and Big Data

In-memory JavaScript DBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

blueflood.io

www.geomesa.org

griddb.net

github.com/techfort/LokiJS

Technical documentation

github.com/rax-maas/blueflood/wiki

www.geomesa.org/documentation/stable/user/index.html

docs.griddb.net

techfort.github.io/LokiJS

Developer

Rackspace

CCRi and others

Toshiba Corporation

Initial release

2013

2014

2013

2014

Current release

4.0.5, February 2024

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Scala

C++

JavaScript

Server operating systems

Linux
OS X

Linux

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

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

yes

via views

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

HTTP REST

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JavaScript API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

depending on storage layer

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

depending on storage layer

Immediate consistency within container, eventual consistency across containers

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID at container level

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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