DBMS > Milvus vs. Sadas Engine vs. SpatiaLite vs. Teradata Aster vs. YDB

System Properties Comparison Milvus vs. Sadas Engine vs. SpatiaLite vs. Teradata Aster vs. YDB

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A DBMS designed for efficient storage of vector data and vector similarity searches

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Spatial extension of SQLite

Platform for big data analytics on multistructured data sources and types

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

milvus.io

www.sadasengine.com

www.gaia-gis.it/fossil/libspatialite/index

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

milvus.io/docs/overview.md

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

ydb.tech/en/docs

Developer

SADAS s.r.l.

Alessandro Furieri

Teradata

Yandex

Initial release

2019

2006

2008

2005

2019

Current release

2.4.4, May 2024

8.0

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

commercial

Open Source

Apache 2.0; commercial license available

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++, Go

C++

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
Linux
Windows

server-less

Linux

Data scheme

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

Typing

predefined data types such as float or date

Vector, Numeric and String

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.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (YQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C++
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Python
R

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Role based access control and fine grained access rights

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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