DBMS > 4D vs. Alibaba Cloud Table Store vs. Riak KV vs. Snowflake vs. TimescaleDB

System Properties Comparison 4D vs. Alibaba Cloud Table Store vs. Riak KV vs. Snowflake vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Distributed, fault tolerant key-value store

Cloud-based data warehousing service for structured and semi-structured data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Wide column store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.4d.com

www.alibabacloud.com/product/table-store

www.snowflake.com

www.timescale.com

Technical documentation

developer.4d.com

www.alibabacloud.com/help/en/tablestore

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

4D, Inc

Alibaba

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Timescale

Initial release

1984

2016

2009

2014

2017

Current release

v20, April 2023

3.2.0, December 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Server operating systems

OS X
Windows

hosted

Linux
OS X

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

restricted

yes

SQL

Support of SQL

yes

close to SQL 92

yes

full PostgreSQL SQL syntax

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

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

Supported programming languages

4D proprietary IDE
PHP

Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

selectable replication factor

yes

Source-replica replication with hot standby and reads on replicas

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

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Users and groups

Access rights based on subaccounts and tokens

yes, using Riak Security

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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