DBMS > Databend vs. Firebase Realtime Database vs. JaguarDB vs. OpenTSDB

System Properties Comparison Databend vs. Firebase Realtime Database vs. JaguarDB vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Performant, highly scalable DBMS for AI and IoT applications

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Time Series DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

github.com/datafuselabs/databend
www.databend.com

firebase.google.com/products/realtime-database

www.jaguardb.com

opentsdb.net

Technical documentation

docs.databend.com

firebase.google.com/docs/database

www.jaguardb.com/support.html

opentsdb.net/docs/build/html/index.html

Developer

Databend Labs

Google

acquired by Google 2014

DataJaguar, Inc.

currently maintained by Yahoo and other contributors

Initial release

2021

2012

2015

2011

Current release

1.0.59, April 2023

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

Open Source

LGPL

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

Rust

C++

the server part. Clients available in other languages

Java

Server operating systems

hosted
Linux
macOS

hosted

Linux

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

HTTP API
Telnet API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java
JavaScript
Objective-C

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

based on HBase

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.

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes, based on authentication and database rules

rights management via user accounts

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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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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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