DBMS > DolphinDB vs. Hypertable vs. OrigoDB vs. Valentina Server

System Properties Comparison DolphinDB vs. Hypertable vs. OrigoDB vs. Valentina Server

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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

A fully ACID in-memory object graph database

Object-relational database and reports server

Primary database model

Time Series DBMS

Wide column store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.dolphindb.com

origodb.com

www.valentina-db.net

Technical documentation

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

origodb.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

DolphinDB, Inc

Hypertable Inc.

Robert Friberg et al

Paradigma Software

Initial release

2018

2009

under the name LiveDB

1999

Current release

v2.00.4, January 2022

0.9.8.11, March 2016

5.7.5

License

Commercial or Open Source

commercial

free community version available

Open Source

GNU version 3. Commercial license available

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

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

.NET Client API
HTTP API
LINQ

ODBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

.Net

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

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

depending on model

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

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