DBMS > Apache Druid vs. Hawkular Metrics vs. Immudb vs. Microsoft SQL Server

System Properties Comparison Apache Druid vs. Hawkular Metrics vs. Immudb vs. Microsoft SQL Server

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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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Microsofts flagship relational DBMS

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

druid.apache.org

www.hawkular.org

github.com/codenotary/immudb
immudb.io

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

Technical documentation

druid.apache.org/docs/latest/design

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.immudb.io

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

Developer

Apache Software Foundation and contributors

Community supported by Red Hat

Codenotary

Microsoft

Initial release

2012

2014

2020

1989

Current release

29.0.1, April 2024

1.2.3, April 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
Windows

Data scheme

yes

schema-less columns are supported

schema-free

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 syntax

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP REST

gRPC protocol
PostgreSQL wire protocol

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

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

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

based on Cassandra

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

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