DBMS > Databricks vs. FoundationDB vs. OrigoDB vs. SAP HANA vs. Sqrrl

System Properties Comparison Databricks vs. FoundationDB vs. OrigoDB vs. SAP HANA vs. Sqrrl

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

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.

Ordered key-value store. Core features are complimented by layers.

A fully ACID in-memory object graph database

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store
Object oriented DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.databricks.com

github.com/apple/foundationdb

origodb.com

www.sap.com/products/hana.html

sqrrl.com

Technical documentation

docs.databricks.com

apple.github.io/foundationdb

origodb.com/docs

help.sap.com/hana

Developer

Databricks

FoundationDB

Robert Friberg et al

SAP

Amazon

originally Sqrrl Data, Inc.

Initial release

2013

2009

under the name LiveDB

2010

2012

Current release

6.2.28, November 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

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

Implementation language

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Appliance or cloud-service

Linux

Data scheme

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

schema-free

some layers support schemas

yes

schema-free

Typing

predefined data types such as float or date

some layers support typing

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

supported in specific SQL layer only

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Python
R
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions and aggregates

in SQL-layer only

yes

SQLScript, R

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

in SQL-layer only

depending on model

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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 authorization

yes

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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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