DBMS > Apache Druid vs. Hawkular Metrics vs. Prometheus vs. SpaceTime vs. XTDB

System Properties Comparison Apache Druid vs. Hawkular Metrics vs. Prometheus vs. SpaceTime vs. XTDB

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.

Open-source Time Series DBMS and monitoring system

SpaceTime is a spatio-temporal DBMS with a focus on performance.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Spatial DBMS

Document store

Secondary database models

Relational 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	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

druid.apache.org

www.hawkular.org

prometheus.io

www.mireo.com/spacetime

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

druid.apache.org/docs/latest/design

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

prometheus.io/docs

www.xtdb.com/docs

Developer

Apache Software Foundation and contributors

Community supported by Red Hat

Mireo

Juxt Ltd.

Initial release

2012

2014

2015

2020

2019

Current release

29.0.1, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

MIT License

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

Java

C++

Clojure

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Linux
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

yes, extensible-data-notation format

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

A subset of ANSI SQL is implemented

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP REST

RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C#
C++
Python

Clojure
Java

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

based on Cassandra

Sharding

Fixed-grid hypercubes

none

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

by Federation

Real-time block device replication (DRBD)

yes, each node contains all data

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

none

Immediate Consistency

Foreign keys

Referential integrity

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid | by Zisis Flokas
18 October 2021, Towards Data Science

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

Exadata Real-Time Insight - Quick Start
3 April 2024, Oracle

OpenTelemetry vs. Prometheus: You can’t fix what you can’t see
29 March 2024, IBM

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

provided by Google News

Share this page