DBMS > DolphinDB vs. Microsoft SQL Server vs. Newts vs. Sqrrl

System Properties Comparison DolphinDB vs. Microsoft SQL Server vs. Newts vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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.

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.dolphindb.com

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

opennms.github.io/newts

sqrrl.com

Technical documentation

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

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

github.com/OpenNMS/newts/wiki

Developer

DolphinDB, Inc

Microsoft

OpenNMS Group

Amazon

originally Sqrrl Data, Inc.

Initial release

2018

1989

2014

2012

Current release

v2.00.4, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free community version available

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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

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
OLE DB
Tabular Data Stream (TDS)

HTTP REST
Java API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

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

Java

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

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

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

Sharding

based on Cassandra

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

based on Cassandra

selectable replication factor

making use of Hadoop

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

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Atomic updates per row, document, or graph entity

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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