DBMS > DolphinDB vs. Microsoft Azure SQL Database vs. OrigoDB vs. TempoIQ

System Properties Comparison DolphinDB vs. Microsoft Azure SQL Database vs. OrigoDB vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be 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.

Database as a Service offering with high compatibility to Microsoft SQL Server

A fully ACID in-memory object graph database

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Website

www.dolphindb.com

azure.microsoft.com/en-us/products/azure-sql/database

origodb.com

tempoiq.com (offline)

Technical documentation

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

docs.microsoft.com/en-us/azure/azure-sql

origodb.com/docs

Developer

DolphinDB, Inc

Microsoft

Robert Friberg et al

TempoIQ

Initial release

2018

2010

2009

under the name LiveDB

2012

Current release

v2.00.4, January 2022

V12

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

commercial

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++

Server operating systems

Linux
Windows

hosted

Linux
Windows

Data scheme

yes

schema-free

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.

yes

can be achieved using .NET

Secondary indexes

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

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL

yes

Triggers

yes

Domain Events

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

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

depending on model

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

fine grained access rights according to SQL-standard

Role based authorization

simple authentication-based access control

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