DBMS > Blueflood vs. dBASE vs. Microsoft Azure Cosmos DB vs. TDengine vs. Typesense

System Properties Comparison Blueflood vs. dBASE vs. Microsoft Azure Cosmos DB vs. TDengine vs. Typesense

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS and big data platform

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Search engine

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	9.70
Rank	#44	Overall
	#28	Relational DBMS

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

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	0.76
Rank	#219	Overall
	#14	Search engines

Website

blueflood.io

www.dbase.com

azure.microsoft.com/services/cosmos-db

github.com/taosdata/TDengine
tdengine.com

typesense.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.dbase.com/support/knowledgebase

learn.microsoft.com/azure/cosmos-db

docs.tdengine.com

typesense.org/docs

Developer

Rackspace

Asthon Tate

Microsoft

TDEngine, previously Taos Data

Initial release

2013

1979

2014

2019

2015

Current release

dBASE 2019, 2019

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL V3, also commercial editions available

Open Source

GPL V3

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++

Server operating systems

Linux
OS X

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
Windows

Linux

Data scheme

predefined scheme

yes

schema-free

yes

schema-free

pre-defined schema optional

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP REST

none

The IDE can access other DBMS or ODBC-sources.

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

JDBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

dBase proprietary IDE

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

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

JavaScript

Triggers

JavaScript

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

Implicit feature of the cloud service

yes

Multi-source replication using RAFT

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Multi-item ACID transactions with snapshot isolation within a partition

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 for users and roles

Access rights can be defined down to the item level

yes

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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