DBMS > DolphinDB vs. Greenplum vs. Microsoft SQL Server vs. Oracle NoSQL vs. Sequoiadb

System Properties Comparison DolphinDB vs. Greenplum vs. Microsoft SQL Server vs. Oracle NoSQL vs. Sequoiadb

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Microsofts flagship relational DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

www.dolphindb.com

greenplum.org

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

www.oracle.com/database/nosql/technologies/nosql

www.sequoiadb.com

Technical documentation

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

docs.greenplum.org

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

DolphinDB, Inc

Pivotal Software Inc.

Microsoft

Oracle

Sequoiadb Ltd.

Initial release

2018

2005

1989

2011

2013

Current release

v2.00.4, January 2022

7.0.0, September 2023

SQL Server 2022, November 2022

24.1, May 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

Linux
Windows

Linux

Linux
Windows

Linux
Solaris SPARC/x86

Linux

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

oid, date, timestamp, binary, regex

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

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

JDBC
ODBC

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

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

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

C
Java
Perl
Python
R

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

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

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, but depending on the SQL-Server Edition

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

configurable

ACID within a storage node (=shard)

Document is locked during a transaction

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

off heap cache

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access rights for users and roles

simple password-based access control

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