DBMS > Apache Druid vs. HarperDB vs. Microsoft SQL Server vs. MySQL vs. OpenEdge

System Properties Comparison Apache Druid vs. HarperDB vs. Microsoft SQL Server vs. MySQL vs. OpenEdge

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Microsofts flagship relational DBMS

Widely used open source RDBMS

Application development environment with integrated database management system

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
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	0.60
Rank	#244	Overall
	#38	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

druid.apache.org

www.harperdb.io

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

www.mysql.com

www.progress.com/openedge

Technical documentation

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

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

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Apache Software Foundation and contributors

HarperDB

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Initial release

2012

2017

1989

1995

1984

Current release

29.0.1, April 2024

3.1, August 2021

SQL Server 2022, November 2022

8.4.0, April 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community edition available

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Node.js

C++

C and C++

Server operating systems

Linux
OS X
Unix

Linux
OS X

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-less columns are supported

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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 data manipulation statements

yes

with proprietary extensions

yes

close to SQL 92

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

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

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

A table resides as a whole on one (or more) nodes in a cluster

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Users and groups

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