DBMS > Databricks vs. Datastax Enterprise vs. Fauna vs. SAP HANA

System Properties Comparison Databricks vs. Datastax Enterprise vs. Fauna vs. SAP HANA

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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.

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Relational DBMS

Wide column store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.databricks.com

www.datastax.com/products/datastax-enterprise

fauna.com

www.sap.com/products/hana.html

Technical documentation

Developer

Databricks

DataStax

Fauna, Inc.

SAP

Initial release

2013

2011

2014

2010

Current release

6.8, April 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

hosted

Linux
OS X

hosted

Appliance or cloud-service

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

SQL-like DML and DDL statements (CQL); Spark SQL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Python
R
Scala

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

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

Identity management, authentication, and 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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DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.