DBMS > FeatureBase vs. Oracle Rdb vs. RocksDB

System Properties Comparison FeatureBase vs. Oracle Rdb vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

Primary database model

Relational DBMS

Key-value store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.featurebase.com

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

rocksdb.org

Technical documentation

docs.featurebase.com

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

github.com/facebook/rocksdb/wiki

Developer

Molecula and Pilosa Open Source Contributors

Oracle, originally developed by Digital Equipment Corporation (DEC)

Facebook, Inc.

Initial release

2017

1984

2013

Current release

2022, May 2022

7.4.1.1, 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
macOS

HP Open VMS

Linux

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

C++ API
Java API

Supported programming languages

Java
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

Transaction concepts

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

yes

yes, on a single node

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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

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