DBMS > AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Postgres-XL vs. Tarantool

System Properties Comparison AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Postgres-XL vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	0.62
Rank	#241	Overall
	#110	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

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

Website

alasql.org

www.alibabacloud.com/product/hybriddb-postgresql

www.postgres-xl.org

www.tarantool.io

Technical documentation

github.com/AlaSQL/alasql

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.postgres-xl.org/documentation

www.tarantool.io/en/doc

Developer

Andrey Gershun & Mathias R. Wulff

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Initial release

2014

2016

2014

since 2012, originally named StormDB

2008

Current release

10 R1, October 2018

2.10.0, May 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Mozilla public license

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

JavaScript

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux
macOS

BSD
Linux
macOS

Data scheme

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

distributed, parallel query execution

Full-featured ANSI SQL support

APIs and other access methods

JavaScript API

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Open binary protocol

Supported programming languages

JavaScript

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

user defined functions

Lua, C and SQL stored procedures

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

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

none

yes

Implicit feature of the cloud service

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

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

only for local storage and DOM-storage

ACID

MVCC

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

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

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

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

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