DBMS > DolphinDB vs. Microsoft Azure Synapse Analytics vs. Newts vs. Qdrant

System Properties Comparison DolphinDB vs. Microsoft Azure Synapse Analytics vs. Newts vs. Qdrant

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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.

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

Time Series DBMS based on Cassandra

A high-performance vector database with neural network or semantic-based matching

Primary database model

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	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

www.dolphindb.com

azure.microsoft.com/services/synapse-analytics

opennms.github.io/newts

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

github.com/OpenNMS/newts/wiki

qdrant.tech/documentation

Developer

DolphinDB, Inc

Microsoft

OpenNMS Group

Qdrant

Initial release

2018

2016

2014

2021

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Rust

Server operating systems

Linux
Windows

hosted

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

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

HTTP REST
Java API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

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

C#
Java
PHP

Java

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, horizontal partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

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

yes

Key-based authentication

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