DBMS > Databricks vs. GBase vs. InfluxDB vs. SAP HANA

System Properties Comparison Databricks vs. GBase vs. InfluxDB 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.

An analytical database for business intelligence with large customers in China.

DBMS for storing time series, events and metrics

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.databricks.com

www.gbase.cn

www.influxdata.com/products/influxdb-overview

www.sap.com/products/hana.html

Technical documentation

docs.databricks.com

docs.influxdata.com/influxdb

help.sap.com/hana

Developer

Databricks

SAP

Initial release

2013

2010

Current release

GBase 8a

2.7.6, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Linux
OS X

through Homebrew

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

Numeric data and Strings

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 query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API
JSON over UDP

JDBC
ODBC

Supported programming languages

Python
R
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

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

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

Depending on used storage engine

yes

User concepts

Access control

simple rights management via user accounts

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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