DBMS > Blueflood vs. JaguarDB vs. PouchDB vs. Snowflake vs. TDengine

System Properties Comparison Blueflood vs. JaguarDB vs. PouchDB vs. Snowflake vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Performant, highly scalable DBMS for AI and IoT applications

JavaScript DBMS with an API inspired by CouchDB

Cloud-based data warehousing service for structured and semi-structured data

Time Series DBMS and big data platform

Primary database model

Time Series DBMS

Key-value store
Vector DBMS

Document store

Relational DBMS

Time Series 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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.jaguardb.com/support.html

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Rackspace

DataJaguar, Inc.

Apache Software Foundation

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2013

2015

2012

2014

2019

Current release

3.3 July 2023

7.1.1, June 2019

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

Open Source

commercial

Open Source

AGPL V3, also commercial editions available

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++

the server part. Clients available in other languages

JavaScript

Server operating systems

Linux
OS X

Linux

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

hosted

Linux
Windows

Data scheme

predefined scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP REST

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

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

JavaScript

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

Eventual Consistency

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

by using IndexedDB, WebSQL or LevelDB as backend

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

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Streamlining Time-Series Data Management with TDengine’s PostgreSQL Connector
12 June 2024

Enhancing IoT and Industrial Data Management with TDengine’s MySQL Connector
12 June 2024

Comprehensive Comparison Between TDengine and MongoDB
6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

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