DBMS > Alibaba Cloud MaxCompute vs. CockroachDB vs. Faircom DB vs. SQLite

System Properties Comparison Alibaba Cloud MaxCompute vs. CockroachDB vs. Faircom DB vs. SQLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

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

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.cockroachlabs.com

www.faircom.com/products/faircom-db

www.sqlite.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.cockroachlabs.com/docs

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

www.sqlite.org/docs.html

Developer

Alibaba

Cockroach Labs

FairCom Corporation

Dwayne Richard Hipp

Initial release

2016

2015

1979

2000

Current release

24.1.0, May 2024

V12, November 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

commercial

Restricted, free version available

Open Source

Public Domain

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

ANSI C, C++

Server operating systems

hosted

Linux
macOS
Windows

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

easily portable to other OSs

server-less

Data scheme

yes

dynamic schema

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

SQL-like query language

yes, wire compatible with PostgreSQL

yes, ANSI SQL with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication using RAFT

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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Role-based access control

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.