DBMS > Databricks vs. EJDB vs. Lovefield vs. OrigoDB vs. SAP SQL Anywhere

System Properties Comparison Databricks vs. EJDB vs. Lovefield vs. OrigoDB vs. SAP SQL Anywhere

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Embeddable relational database for web apps written in pure JavaScript

A fully ACID in-memory object graph database

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Document store
Object oriented DBMS

Relational 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	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.databricks.com

github.com/Softmotions/ejdb

google.github.io/lovefield

origodb.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.databricks.com

github.com/Softmotions/ejdb/blob/master/README.md

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Databricks

Softmotions

Google

Robert Friberg et al

SAP

formerly Sybase

Initial release

2013

2012

2014

2009

under the name LiveDB

1992

Current release

2.1.12, February 2017

17, July 2015

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Server operating systems

hosted

server-less

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

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

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

.NET Client API
HTTP API
LINQ

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Python
R
Scala

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

JavaScript

.Net

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

yes, in C/C++, Java, .Net or Perl

Triggers

Using read-only observers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Database mirroring

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

typically not needed, however similar functionality with collection joins possible

yes

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

Role based authorization

fine grained access rights according to SQL-standard

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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