DBMS > OrigoDB vs. Transwarp Hippo

System Properties Comparison OrigoDB vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A fully ACID in-memory object graph database

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

Primary database model

Document store
Object oriented DBMS

Vector DBMS

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

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.00
Rank	#392	Overall
	#14	Vector DBMS

Website

origodb.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

origodb.com/docs

Developer

Robert Friberg et al

Initial release

2009

under the name LiveDB

2023

Current release

1.0, May 2023

License

Commercial or Open Source

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux
Windows

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

.NET Client API
HTTP API
LINQ

RESTful HTTP API

Supported programming languages

.Net

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

depending on model

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

Write ahead log

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 authorization

Role based access control and fine grained access rights

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

Share this page