DBMS > ArcadeDB vs. Databricks vs. Microsoft Azure Synapse Analytics vs. TinkerGraph

System Properties Comparison ArcadeDB vs. Databricks vs. Microsoft Azure Synapse Analytics vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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.

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store
Relational DBMS

Relational DBMS

Graph DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

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

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

arcadedb.com

www.databricks.com

azure.microsoft.com/services/synapse-analytics

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.arcadedb.com

docs.databricks.com

docs.microsoft.com/azure/synapse-analytics

Developer

Arcade Data

Databricks

Microsoft

Initial release

2021

2013

2016

2009

Current release

September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

All OS with a Java VM

hosted

Data scheme

schema-free

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

yes

schema-free

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

SQL-like query language, no joins

with Databricks SQL

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

TinkerPop 3

Supported programming languages

Java

Python
R
Scala

C#
Java
PHP

Groovy
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

relationship in graphs

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

yes

Relationships in graphs

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

optional

In-memory capabilities

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

yes

User concepts

Access control

yes

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

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