DBMS > Apache Druid vs. DolphinDB vs. EXASOL vs. Microsoft SQL Server vs. Transwarp StellarDB

System Properties Comparison Apache Druid vs. DolphinDB vs. EXASOL vs. Microsoft SQL Server vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Microsofts flagship relational DBMS

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Graph DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

druid.apache.org

www.dolphindb.com

www.exasol.com

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

www.transwarp.cn/en/product/stellardb

Technical documentation

druid.apache.org/docs/latest/design

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

www.exasol.com/resources

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

Developer

Apache Software Foundation and contributors

DolphinDB, Inc

Exasol

Microsoft

Transwarp

Initial release

2012

2018

2000

1989

Current release

30.0.0, June 2024

v2.00.4, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community version available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Data scheme

yes

schema-less columns are supported

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

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

.Net
JDBC
ODBC
WebSocket

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

OpenCypher

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Java
Lua
Python
R

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

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Administrators, Users, Groups

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

yes

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