DBMS > DolphinDB vs. Hypertable vs. Microsoft Azure AI Search vs. Transbase

System Properties Comparison DolphinDB vs. Hypertable vs. Microsoft Azure AI Search vs. Transbase

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

Search-as-a-service for web and mobile app development

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Relational DBMS

Vector DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.dolphindb.com

azure.microsoft.com/en-us/services/search

www.transaction.de/en/products/transbase.html

Technical documentation

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

learn.microsoft.com/en-us/azure/search

www.transaction.de/en/products/transbase/features.html

Developer

DolphinDB, Inc

Hypertable Inc.

Microsoft

Transaction Software GmbH

Initial release

2018

2009

2015

1987

Current release

v2.00.4, January 2022

0.9.8.11, March 2016

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

GNU version 3. Commercial license available

commercial

free development license

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

C++

C and C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

an inofficial Windows port is available

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data 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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

C++ API
Thrift

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

User concepts

Access control

Administrators, Users, Groups

yes

using Azure authentication

fine grained access rights according to SQL-standard

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