DBMS > Databricks vs. Dgraph vs. SQL.JS vs. Tkrzw vs. Yaacomo

System Properties Comparison Databricks vs. Dgraph vs. SQL.JS vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is 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.

Distributed and scalable native Graph DBMS

Port of SQLite to JavaScript

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

yaacomo.com

Technical documentation

docs.databricks.com

dgraph.io/docs

sql.js.org/documentation/index.html

Developer

Databricks

Dgraph Labs, Inc.

Alon Zakai

enhancements implemented by others

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2013

2016

2012

2020

2009

Current release

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Server operating systems

hosted

Linux
OS X
Windows

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

Linux
macOS

Android
Linux
Windows

Data scheme

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

schema-free

yes

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

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JavaScript API

JDBC
ODBC

Supported programming languages

Python
R
Scala

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

JavaScript

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

none

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

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

except by serializing a db to a file

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

yes

User concepts

Access control

Planned for future releases

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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Recent citations in the news

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21 May 2024, Fortune

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22 May 2024, eWeek

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