DBMS > Databricks vs. GridGain vs. Prometheus vs. SAP HANA

System Properties Comparison Databricks vs. GridGain vs. Prometheus 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.

GridGain is an in-memory computing platform, built on Apache Ignite

Open-source Time Series DBMS and monitoring system

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

Primary database model

Document store
Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

www.databricks.com

www.gridgain.com

prometheus.io

www.sap.com/products/hana.html

Technical documentation

docs.databricks.com

www.gridgain.com/docs/index.html

prometheus.io/docs

help.sap.com/hana

Developer

Databricks

GridGain Systems, Inc.

SAP

Initial release

2013

2007

2015

2010

Current release

GridGain 8.5.1

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

commercial, open source

Open Source

Apache 2.0

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, C++, .Net, Python, REST, SQL

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

Appliance or cloud-service

Data scheme

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

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Python
R
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes (compute grid and cache interceptors can be used instead)

SQLScript, R

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

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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