DBMS > Alibaba Cloud TSDB vs. Dolt vs. HugeGraph vs. Microsoft Access vs. Microsoft Azure Cosmos DB

System Properties Comparison Alibaba Cloud TSDB vs. Dolt vs. HugeGraph vs. Microsoft Access vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

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

A MySQL compatible DBMS with Git-like versioning of data and schema

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.)

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Spatial DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

www.alibabacloud.com/product/hitsdb

github.com/dolthub/dolt
www.dolthub.com

github.com/hugegraph
hugegraph.apache.org

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

azure.microsoft.com/services/cosmos-db

Technical documentation

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

docs.dolthub.com

hugegraph.apache.org/docs

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

Developer

Alibaba

DoltHub Inc

Baidu

Microsoft

Initial release

2018

1992

2014

Current release

0.9

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

commercial

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Windows

Linux
macOS
Unix

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

yes

JSON types

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

also supports composite index and range index

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

HTTP REST

CLI Client
HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
DAO
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Groovy
Java
Python

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

currently in alpha release

asynchronous Gremlin script jobs

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

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

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

but no files for transaction logging

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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 managed on TSDB instance level

Only one user is configurable, and must be specified in the config file at startup

Users, roles and permissions

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

Access rights can be defined down to the item level

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