DBMS > Apache Drill vs. Databricks vs. Sequoiadb vs. Transbase

System Properties Comparison Apache Drill vs. Databricks vs. Sequoiadb vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

NewSQL database with distributed OLTP and SQL

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

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	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

drill.apache.org

www.databricks.com

www.sequoiadb.com

www.transaction.de/en/products/transbase.html

Technical documentation

drill.apache.org/docs

docs.databricks.com

www.sequoiadb.com/en/index.php?m=Files&a=index

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Databricks

Sequoiadb Ltd.

Transaction Software GmbH

Initial release

2012

2013

1987

Current release

1.20.3, January 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Server: AGPL; Client: Apache V2

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

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

with Databricks SQL

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++

Python
R
Scala

.Net
C++
Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

yes

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

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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Apache Drill vs. Apache Spark — Which SQL query engine is better for you?
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Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

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29 May 2024, AccessWire

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21 May 2024, Fortune

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