DBMS > Apache Drill vs. Hive vs. TimescaleDB

System Properties Comparison Apache Drill vs. Hive vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

drill.apache.org

hive.apache.org

www.timescale.com

Technical documentation

drill.apache.org/docs

cwiki.apache.org/confluence/display/Hive/Home

docs.timescale.com

Developer

Apache Software Foundation

initially developed by Facebook

Timescale

Initial release

2012

2017

Current release

1.20.3, January 2023

3.1.3, April 2022

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

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

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

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

Supported programming languages

C++

C++
Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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