DBMS > Oracle Rdb vs. SwayDB vs. Transwarp Hippo

System Properties Comparison Oracle Rdb vs. SwayDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Key-value store

Vector DBMS

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

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

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

swaydb.simer.au

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

Developer

Oracle, originally developed by Digital Equipment Corporation (DEC)

Simer Plaha

Initial release

1984

2018

2023

Current release

7.4.1.1, 2021

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Server operating systems

HP Open VMS

Linux
macOS

Data scheme

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

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

yes

APIs and other access methods

RESTful HTTP API

Supported programming languages

Java
Kotlin
Scala

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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, on a single node

Atomic execution of operations

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

Role based access control and fine grained access rights

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