DBMS > Apache Doris vs. BoltDB vs. Databricks vs. Oracle Rdb vs. RocksDB

System Properties Comparison Apache Doris vs. BoltDB vs. Databricks vs. Oracle Rdb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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 persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store

Document store
Relational DBMS

Relational DBMS

Key-value store

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Trend Chart

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

doris.apache.org
github.com/apache/doris

github.com/boltdb/bolt

www.databricks.com

www.oracle.com/database/technologies/related/rdb.html

rocksdb.org

Technical documentation

github.com/apache/doris/wiki

docs.databricks.com

www.oracle.com/database/technologies/related/rdb-doc.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from Baidu

Databricks

Oracle, originally developed by Digital Equipment Corporation (DEC)

Facebook, Inc.

Initial release

2017

2013

1984

2013

Current release

1.2.2, February 2023

7.4.1.1, 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

hosted

HP Open VMS

Linux

Data scheme

yes

schema-free

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

schema-free

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

yes

with Databricks SQL

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Java

Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes

ACID

yes, on a single node

yes

Concurrency

Support for concurrent manipulation of data

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

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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