DBMS > Amazon DynamoDB vs. jBASE vs. Milvus vs. Weaviate

System Properties Comparison Amazon DynamoDB vs. jBASE vs. Milvus vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A robust multi-value DBMS comprising development tools and middleware

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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Document store
Key-value store

Multivalue DBMS

Vector DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

aws.amazon.com/dynamodb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

milvus.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

milvus.io/docs/overview.md

weaviate.io/developers/weaviate

Developer

Amazon

Rocket Software (formerly Zumasys)

Weaviate B.V.

Initial release

2012

1991

2019

Current release

5.7

2.3.4, January 2024

1.19, May 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

Open Source

commercial license available with Weaviate Enterprise

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++, Go

Server operating systems

hosted

AIX
Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

optional

Vector, Numeric and String

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

Secondary indexes

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

GraphQL is used as query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

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

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights can be defined down to the item level

Role based access control and fine grained access rights

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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All companies that have data.
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Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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