DBMS > Databricks vs. EDB Postgres vs. Infobright vs. SAP HANA vs. WakandaDB

System Properties Comparison Databricks vs. EDB Postgres vs. Infobright vs. SAP HANA vs. WakandaDB

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.

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Relational DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial 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	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.databricks.com

www.enterprisedb.com

ignitetech.com/softwarelibrary/infobrightdb

www.sap.com/products/hana.html

wakanda.github.io

Technical documentation

docs.databricks.com

www.enterprisedb.com/docs

help.sap.com/hana

wakanda.github.io/doc

Developer

Databricks

EnterpriseDB

Ignite Technologies Inc.; formerly InfoBright Inc.

SAP

Wakanda SAS

Initial release

2013

2005

2010

2012

Current release

14, December 2021

2.0 SPS07 (April 4, 2023), April 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

AGPLv3, extended commercial license available

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

C++, JavaScript

Server operating systems

hosted

Linux
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

Flexible Schema (defined schema, partial schema, 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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

with Databricks SQL

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Python
R
Scala

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

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

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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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