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

System Properties Comparison Apache Druid vs. Dragonfly 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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

druid.apache.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.exasol.com

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

www.transwarp.cn/en/product/stellardb

Technical documentation

druid.apache.org/docs/latest/design

www.dragonflydb.io/docs

www.exasol.com/resources

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

Developer

Apache Software Foundation and contributors

DragonflyDB team and community contributors

Exasol

Microsoft

Transwarp

Initial release

2012

2023

2000

1989

Current release

29.0.1, April 2024

1.0, March 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSL 1.1

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

Linux
Windows

Data scheme

yes

schema-less columns are supported

scheme-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protocol

.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#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java
Lua
Python
R

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

Server-side scripts

Stored procedures

Lua

user defined functions

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

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

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

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

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

fine grained access rights according to SQL-standard

yes

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