DBMS > Databricks vs. Dgraph vs. Microsoft Azure Synapse Analytics vs. Valentina Server

System Properties Comparison Databricks vs. Dgraph vs. Microsoft Azure Synapse Analytics vs. Valentina Server

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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.

Distributed and scalable native Graph DBMS

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Object-relational database and reports server

Primary database model

Document store
Relational DBMS

Graph DBMS

Relational DBMS

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

Score	76.33
Rank	#17	Overall
	#3	Document stores
	#11	Relational DBMS

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

www.databricks.com

dgraph.io

azure.microsoft.com/services/synapse-analytics

www.valentina-db.net

Technical documentation

docs.databricks.com

dgraph.io/docs

docs.microsoft.com/azure/synapse-analytics

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Databricks

Dgraph Labs, Inc.

Microsoft

Paradigma Software

Initial release

2013

2016

1999

Current release

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

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

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

ODBC

Supported programming languages

Python
R
Scala

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

C#
Java
PHP

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

yes

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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