DBMS > Databend vs. OrigoDB vs. SvectorDB

System Properties Comparison Databend vs. OrigoDB vs. SvectorDB

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A fully ACID in-memory object graph database

Serverless cloud-native vector database

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Vector DBMS

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

Score	0.27
Rank	#290	Overall
	#130	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#21	Vector DBMS

Website

github.com/datafuselabs/databend
www.databend.com

origodb.com

svectordb.com

Technical documentation

docs.databend.com

origodb.com/docs

www.svectordb.com/docs

Developer

Databend Labs

Robert Friberg et al

SvectorDB

Initial release

2021

2009

under the name LiveDB

2023

Current release

1.0.59, April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

Server operating systems

hosted
Linux
macOS

Linux
Windows

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

string, double, vector

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

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

OpenAPI 3.0, RESTful HTTP API, Python SDK, JavaScript / TypeScript SDK

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

yes

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

Users with fine-grained authorization concept, user roles

Role based authorization

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