DBMS > Apache Pinot vs. Kinetica vs. Microsoft Access vs. MongoDB vs. Weaviate

System Properties Comparison Apache Pinot vs. Kinetica vs. Microsoft Access vs. MongoDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Fully vectorized database across both GPUs and CPUs

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Primary database model

Relational DBMS

Document store

Vector DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

pinot.apache.org

www.kinetica.com

www.microsoft.com/en-us/microsoft-365/access

www.mongodb.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.pinot.apache.org

docs.kinetica.com

developer.microsoft.com/en-us/access

www.mongodb.com/docs/manual

weaviate.io/developers/weaviate

Developer

Apache Software Foundation and contributors

Kinetica

Microsoft

MongoDB, Inc

Weaviate B.V.

Initial release

2015

2012

1992

2009

2019

Current release

1.0.0, September 2023

7.1, August 2021

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

Java

C, C++

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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.

Secondary indexes

yes

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

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

Read-only SQL queries via the MongoDB Atlas SQL Interface

GraphQL is used as query language

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

but no files for transaction logging

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights for users and roles on table level

a simple user-level security was built in till version Access 2003

Access rights for users and roles

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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All companies that have data.
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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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

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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