DBMS > SvectorDB vs. Transwarp StellarDB vs. Typesense

System Properties Comparison SvectorDB vs. Transwarp StellarDB vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

Serverless cloud-native vector database

A distributed graph DBMS built for enterprise-level graph applications

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Vector DBMS

Graph DBMS

Search engine

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

Score	0.00
Rank	#392	Overall
	#19	Vector DBMS

Score	0.00
Rank	#392	Overall
	#41	Graph DBMS

Score	0.82
Rank	#207	Overall
	#14	Search engines

Website

svectordb.com

www.transwarp.cn/en/product/stellardb

typesense.org

Technical documentation

www.svectordb.com/docs

typesense.org/docs

Developer

SvectorDB

Transwarp

Initial release

2023

2015

License

Commercial or Open Source

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

server-less

Linux

Data scheme

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

string, double, vector

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-like query language

APIs and other access methods

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

OpenCypher

RESTful HTTP API

Supported programming languages

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

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

Transaction concepts

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

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

yes

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