DBMS > Apache Drill vs. Firebolt vs. Graphite

System Properties Comparison Apache Drill vs. Firebolt vs. Graphite

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Editorial information provided by DB-Engines

Name

Description

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

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

Score	1.82
Rank	#123	Overall
	#22	Document stores
	#60	Relational DBMS

Score	1.03
Rank	#179	Overall
	#79	Relational DBMS

Score	4.57
Rank	#63	Overall
	#4	Time Series DBMS

Website

drill.apache.org

www.firebolt.io

github.com/graphite-project/graphite-web

Technical documentation

drill.apache.org/docs

docs.firebolt.io

graphite.readthedocs.io

Developer

Apache Software Foundation

Firebolt Analytics Inc.

Chris Davis

Initial release

2012

2020

2006

Current release

1.20.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Server operating systems

Linux
OS X
Windows

hosted

Linux
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.Net
ODBC
RESTful HTTP API

HTTP API
Sockets

Supported programming languages

C++

Go
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

locking

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

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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