DBMS > Databricks vs. PostGIS vs. Sadas Engine vs. XTDB

System Properties Comparison Databricks vs. PostGIS vs. Sadas Engine vs. XTDB

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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.

Spatial extension of PostgreSQL

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Relational DBMS

Spatial DBMS

Relational DBMS

Document store

Secondary database models

Relational DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.databricks.com

postgis.net

www.sadasengine.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.databricks.com

postgis.net/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.xtdb.com/docs

Developer

Databricks

SADAS s.r.l.

Juxt Ltd.

Initial release

2013

2005

2006

2019

Current release

3.4.2, February 2024

8.0

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

commercial

free trial version available

Open Source

MIT License

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++

Clojure

Server operating systems

hosted

AIX
Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

HTTP REST
JDBC

Supported programming languages

Python
R
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

based on PostgreSQL

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

yes

based on PostgreSQL

Access rights for users, groups and roles 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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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Databricks tells investors annualized revenue will reach $2.4 billion at midway point of year
13 June 2024, CNBC

Databricks Launches AI Graphics Competitor to Salesforce, Microsoft
12 June 2024, Yahoo Finance

Legacy data migration to Databricks: Fast transition sitename%%
14 June 2024, SiliconANGLE News

Databricks Data+AI Summit 2024: The Biggest News
12 June 2024, CRN

Why Databricks' Tabular Play Has Put Snowflake On The Defensive
10 June 2024, Forbes

provided by Google News

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