DBMS > Alibaba Cloud TSDB vs. Faircom EDGE vs. HugeGraph vs. Microsoft Access vs. MongoDB

System Properties Comparison Alibaba Cloud TSDB vs. Faircom EDGE vs. HugeGraph vs. Microsoft Access vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Graph DBMS

Relational DBMS

Document store

Secondary database models

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	0.24
Rank	#312	Overall
	#27	Time Series DBMS

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Website

www.alibabacloud.com/product/hitsdb

www.faircom.com/products/faircom-edge

github.com/hugegraph
hugegraph.apache.org

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

www.mongodb.com

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

hugegraph.apache.org/docs

developer.microsoft.com/en-us/access

www.mongodb.com/docs/manual

Developer

Alibaba

FairCom Corporation

Baidu

Microsoft

MongoDB, Inc

Initial release

1979

2018

1992

2009

Current release

V3, October 2020

0.9

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

License

Commercial or Open Source

commercial

Restricted, free version available

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.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

ANSI C, C++

Java

C++

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Unix

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

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.

Typing

predefined data types such as float or date

Numeric data and Strings

yes, ANSI Standard SQL Types

yes

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

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

but not compliant to any SQL standard

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

HTTP REST

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
DAO
ODBC
OLE DB

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Groovy
Java
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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

asynchronous Gremlin script jobs

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

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.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

depending on used storage backend, e.g. Cassandra and HBase

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

when using SQL

yes

edges in graph

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

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional, enabled by default

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access managed on TSDB instance level

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Users, roles and permissions

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

Access rights for users and roles

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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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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