DBMS > Databricks vs. Hive vs. Spark SQL vs. SQLite vs. SWC-DB

System Properties Comparison Databricks vs. Hive vs. Spark SQL vs. SQLite vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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.

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

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

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.databricks.com

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

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

Developer

Databricks

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Dwayne Richard Hipp

Alex Kashirin

Initial release

2013

2012

2014

2000

2020

Current release

3.1.3, April 2022

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

server-less

Linux

Data scheme

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

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

with Databricks SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Proprietary protocol
Thrift

Supported programming languages

Python
R
Scala

C++
Java
PHP
Python

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

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

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

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

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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