DBMS > Alibaba Cloud MaxCompute vs. Faircom DB vs. Qdrant vs. RavenDB vs. Yanza

System Properties Comparison Alibaba Cloud MaxCompute vs. Faircom DB vs. Qdrant vs. RavenDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A high-performance vector database with neural network or semantic-based matching

Open Source Operational and Transactional Enterprise NoSQL Document Database

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Key-value store
Relational DBMS

Vector DBMS

Document store

Time Series DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

www.alibabacloud.com/product/maxcompute

www.faircom.com/products/faircom-db

github.com/qdrant/qdrant
qdrant.tech

ravendb.net

yanza.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

qdrant.tech/documentation

ravendb.net/docs

Developer

Alibaba

FairCom Corporation

Qdrant

Hibernating Rhinos

Yanza

Initial release

2016

1979

2021

2010

2015

Current release

V12, November 2020

5.4, July 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

Rust

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Docker
Linux
macOS
Windows

Linux
macOS
Raspberry Pi
Windows

Windows

Data scheme

yes

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

yes, ANSI SQL with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

.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

Supported programming languages

Java

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Collection-level replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency, tunable 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.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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 rights for users and roles

Fine grained access rights according to SQL-standard with additional protections for files

Key-based authentication

Authorization levels configured per client per database

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