DBMS > DolphinDB vs. GeoSpock vs. Microsoft SQL Server

System Properties Comparison DolphinDB vs. GeoSpock vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded 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.

Spatial and temporal data processing engine for extreme data scale

Microsofts flagship relational DBMS

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

www.dolphindb.com

geospock.com

www.microsoft.com/en-us/sql-server

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

Developer

DolphinDB, Inc

GeoSpock

Microsoft

Initial release

2018

1989

Current release

v2.00.4, January 2022

2.0, September 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free community version available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Javascript

C++

Server operating systems

Linux
Windows

hosted

Linux
Windows

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.

yes

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

SQL-like query language

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

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

JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

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

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

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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