DBMS > Alibaba Cloud MaxCompute vs. Firebird vs. Google BigQuery vs. MarkLogic

System Properties Comparison Alibaba Cloud MaxCompute vs. Firebird vs. Google BigQuery vs. MarkLogic

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Name

Description

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

Firebird is an open source RDBMS forked from Borland's InterBase

Large scale data warehouse service with append-only tables

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

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

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Website

www.alibabacloud.com/product/maxcompute

www.firebirdsql.org

cloud.google.com/bigquery

www.progress.com/marklogic

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

www.progress.com/marklogic/documentation

Developer

Alibaba

Firebird Foundation

Google

MarkLogic Corp.

Initial release

2016

2000

As fork of Borland's InterBase

2010

2001

Current release

5.0.1, August 2024

11.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

commercial

restricted free version is available

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

C and C++

C++

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL92

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

Java

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

PSQL

user defined functions

in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes, with Range Indexes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control at the document and subdocument levels

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