DBMS > Blueflood vs. DolphinDB vs. Firebase Realtime Database vs. GeoMesa

System Properties Comparison Blueflood vs. DolphinDB vs. Firebase Realtime Database vs. GeoMesa

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Primary database model

Time Series DBMS

Document store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Website

blueflood.io

www.dolphindb.com

firebase.google.com/products/realtime-database

www.geomesa.org

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.dolphindb.cn/en/help200/index.html

firebase.google.com/docs/database

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

Developer

Rackspace

DolphinDB, Inc

Google

acquired by Google 2014

CCRi and others

Initial release

2013

2018

2012

2014

Current release

v2.00.4, January 2022

5.0.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community version available

commercial

Open Source

Apache License 2.0

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

C++

Scala

Server operating systems

Linux
OS X

Linux
Windows

hosted

Data scheme

predefined 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP REST

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

depending on storage layer

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

depending on storage layer

User concepts

Access control

Administrators, Users, Groups

yes, based on authentication and database rules

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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