DBMS > Alibaba Cloud PolarDB vs. Cassandra vs. Google Cloud Firestore vs. Manticore Search vs. Microsoft Access

System Properties Comparison Alibaba Cloud PolarDB vs. Cassandra vs. Google Cloud Firestore vs. Manticore Search vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Description

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Multi-storage database for search, including full-text search.

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.)

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.66
Rank	#235	Overall
	#108	Relational DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Website

www.alibabacloud.com/product/polardb

cassandra.apache.org

firebase.google.com/products/firestore

manticoresearch.com

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

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

cassandra.apache.org/doc/latest

firebase.google.com/docs/firestore

manual.manticoresearch.com

developer.microsoft.com/en-us/access

Developer

Alibaba

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Manticore Software

Microsoft

Initial release

2008

2017

1992

Current release

4.1.3, July 2023

6.0, February 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

GPL version 2

commercial

Bundled with Microsoft Office

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

hosted

FreeBSD
Linux
macOS
Windows

Windows

Not a real database server, but making use of DLLs

Data scheme

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

Can index from XML

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

user defined functions

yes

since Access 2010 using the ACE-engine

Triggers

yes

yes, with Cloud Functions

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

but no files for transaction logging

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

Access rights for users can be defined per object

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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