DBMS > Blueflood vs. Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Oracle Rdb vs. TDengine

System Properties Comparison Blueflood vs. Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Oracle Rdb vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Globally distributed, horizontally scalable, multi-model database service

Widely used in-process key-value store

Time Series DBMS and big data platform

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

blueflood.io

azure.microsoft.com/services/cosmos-db

www.oracle.com/database/technologies/related/berkeleydb.html

www.oracle.com/database/technologies/related/rdb.html

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/rax-maas/blueflood/wiki

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/cd/E17076_05/html/index.html

www.oracle.com/database/technologies/related/rdb-doc.html

docs.tdengine.com

Developer

Rackspace

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

TDEngine, previously Taos Data

Initial release

2013

2014

1994

1984

2019

Current release

18.1.40, May 2020

7.4.1.1, 2021

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial license available

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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

HP Open VMS

Linux
Windows

Data scheme

predefined scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

JSON types

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

only with the Berkeley DB XML edition

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP REST

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
RESTful HTTP API

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

yes

only for the SQL API

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

yes, on a single node

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 can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

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