DBMS > Databricks vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. searchxml

System Properties Comparison Databricks vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. searchxml

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.

Database as a Service offering with high compatibility to Microsoft SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Native XML DBMS
Search engine

Secondary database models

Document store
Graph DBMS
Spatial 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	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.databricks.com

azure.microsoft.com/en-us/products/azure-sql/database

nsdb.io

origodb.com

www.searchxml.net/category/products

Technical documentation

docs.databricks.com

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

origodb.com/docs

www.searchxml.net/support/handouts

Developer

Databricks

Microsoft

Robert Friberg et al

informationpartners gmbh

Initial release

2013

2010

2017

2009

under the name LiveDB

2015

Current release

V12

1.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

commercial

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++

Java, Scala

C++

Server operating systems

hosted

Linux
macOS

Linux
Windows

Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

with Databricks SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Python
R
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Scala

.Net

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions and aggregates

Transact SQL

yes

on the application server

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

Source-replica replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Recent citations in the news

Databricks vs. Redshift: Data Platform Comparison
22 May 2024, eWeek

XponentL Data Secures Strategic Investment from Databricks Ventures to Fuel Data Transformation & Generative AI
22 May 2024, businesswire.com

XponentL Data Receives Strategic Investment from Databricks Ventures and Inoca Capital Partners
22 May 2024, FinSMEs

Introducing the Databricks AI Fund
22 May 2024, CXOToday.com

Databricks is expanding the scope of its AI investments with second VC fund
21 May 2024, Fortune

provided by Google News

Public Preview: New Azure SQL Database skills introduced to Microsoft Copilot in Azure | Azure updates
21 May 2024, azure.microsoft.com

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, Oracle

Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers
25 April 2024, Microsoft

provided by Google News

Share this page