DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Firestore vs. LeanXcale vs. Tarantool

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Firestore vs. LeanXcale vs. Tarantool

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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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

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

Document store

Key-value store
Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.78
Rank	#221	Overall
	#102	Relational DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

firebase.google.com/products/firestore

www.leanxcale.com

www.tarantool.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

firebase.google.com/docs/firestore

www.tarantool.io/en/doc

Developer

Alibaba

Google

LeanXcale

Initial release

2016

2017

2015

2008

Current release

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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++

Server operating systems

hosted

BSD
Linux
macOS

Data scheme

yes

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

through Apache Derby

Full-featured ANSI SQL support

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Open binary protocol

Supported programming languages

Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
Java
Scala

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Java

yes, Firebase Rules & Cloud Functions

Lua, C and SQL stored procedures

Triggers

yes, with Cloud Functions

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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