DBMS > Apache Drill vs. Firebird vs. Hawkular Metrics vs. IBM Cloudant vs. TimescaleDB

System Properties Comparison Apache Drill vs. Firebird vs. Hawkular Metrics vs. IBM Cloudant vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

Firebird is an open source RDBMS forked from Borland's InterBase

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

Database as a Service offering based on Apache CouchDB

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

drill.apache.org

www.firebirdsql.org

www.hawkular.org

www.ibm.com/products/cloudant

www.timescale.com

Technical documentation

drill.apache.org/docs

www.firebirdsql.org/en/reference-manuals

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

cloud.ibm.com/docs/Cloudant

docs.timescale.com

Developer

Apache Software Foundation

Firebird Foundation

Community supported by Red Hat

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Timescale

Initial release

2012

2000

As fork of Borland's InterBase

2014

2010

2017

Current release

1.20.3, January 2023

5.0.0, January 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Erlang

Server operating systems

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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 SELECT statement is SQL:2003 compliant

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP REST

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C++

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Go
Java
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

PSQL

View functions (Map-Reduce) in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Optimistic locking

yes

Durability

Support for making data persistent

Depending on the underlying data source

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

Users with fine-grained authorization concept

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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