DBMS > DolphinDB vs. HyperSQL vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics

System Properties Comparison DolphinDB vs. HyperSQL vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

www.dolphindb.com

hsqldb.org

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

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

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

docs.microsoft.com/azure/synapse-analytics

Developer

DolphinDB, Inc

Microsoft

Initial release

2018

2001

2015

2016

Current release

v2.00.4, January 2022

2.7.2, June 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

based on BSD license

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++

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Data scheme

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

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

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Python

C#
Java
PHP

Server-side scripts

Stored procedures

yes

Java, SQL

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

yes

using Azure authentication

yes

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