DBMS > Databricks vs. EJDB vs. JaguarDB vs. OpenEdge vs. Sequoiadb

System Properties Comparison Databricks vs. EJDB vs. JaguarDB vs. OpenEdge vs. Sequoiadb

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)

Performant, highly scalable DBMS for AI and IoT applications

Application development environment with integrated database management system

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Relational DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

Document store
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	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.databricks.com

github.com/Softmotions/ejdb

www.jaguardb.com

www.progress.com/openedge

www.sequoiadb.com

Technical documentation

docs.databricks.com

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

www.jaguardb.com/support.html

documentation.progress.com/output/ua/OpenEdge_latest

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Databricks

Softmotions

DataJaguar, Inc.

Progress Software Corporation

Sequoiadb Ltd.

Initial release

2013

2012

2015

1984

2013

Current release

3.3 July 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

GPL V3.0

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

server-less

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

oid, date, timestamp, binary, regex

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

close to SQL 92

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

Python
R
Scala

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Progress proprietary ABL (Advanced Business Language)

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

User concepts

Access control

rights management via user accounts

Users and groups

simple password-based access control

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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