DBMS > Apache Drill vs. Hawkular Metrics vs. JanusGraph vs. STSdb

System Properties Comparison Apache Drill vs. Hawkular Metrics vs. JanusGraph vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Time Series DBMS

Graph DBMS

Key-value store

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

drill.apache.org

www.hawkular.org

janusgraph.org

github.com/STSSoft/STSdb4

Technical documentation

drill.apache.org/docs

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

docs.janusgraph.org

Developer

Apache Software Foundation

Community supported by Red Hat

Linux Foundation; originally developed as Titan by Aurelius

STS Soft SC

Initial release

2012

2014

2017

2011

Current release

1.20.3, January 2023

1.0.0, October 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

.NET Client API

Supported programming languages

C++

Go
Java
Python
Ruby

Clojure
Java
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Depending on the underlying data source

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

User authentification and security via Rexster Graph Server

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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5 June 2019, DevClass

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12 October 2020, Towards Data Science

Database Deep Dives: JanusGraph
8 August 2019, IBM

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

provided by Google News

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