DBMS > Microsoft SQL Server vs. RavenDB vs. Riak KV vs. Weaviate

System Properties Comparison Microsoft SQL Server vs. RavenDB vs. Riak KV vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed, fault tolerant key-value store

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

Primary database model

Relational DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.microsoft.com/en-us/sql-server

ravendb.net

github.com/weaviate/weaviate
weaviate.io

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

ravendb.net/docs

www.tiot.jp/riak-docs/riak/kv/latest

weaviate.io/developers/weaviate

Developer

Microsoft

Hibernating Rhinos

OpenSource, formerly Basho Technologies

Weaviate B.V.

Initial release

1989

2010

2009

2019

Current release

SQL Server 2022, November 2022

5.4, July 2022

3.2.0, December 2022

1.19, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

Open Source

Apache version 2, commercial enterprise edition

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

Server operating systems

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

Data scheme

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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

restricted

yes

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

SQL

Support of SQL

yes

SQL-like query language (RQL)

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Multi-source replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

yes, using Riak Security

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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