DBMS > 4D vs. Apache Kylin vs. ToroDB vs. Vertica vs. YTsaurus

System Properties Comparison 4D vs. Apache Kylin vs. ToroDB vs. Vertica vs. YTsaurus

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS

Document store

Relational DBMS

Column oriented

Document store
Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	0.11
Rank	#340	Overall
	#45	Document stores
	#50	Key-value stores

Website

www.4d.com

kylin.apache.org

github.com/torodb/server

www.vertica.com

ytsaurus.tech

Technical documentation

developer.4d.com

kylin.apache.org/docs

vertica.com/documentation

ytsaurus.tech/docs/en

Developer

4D, Inc

Apache Software Foundation, originally contributed from eBay Inc

8Kdata

OpenText

previously Micro Focus and Hewlett Packard

Yandex

Initial release

1984

2015

2016

2005

2023

Current release

v20, April 2023

3.1.0, July 2020

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL-V3

commercial

Limited community edition free

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

OS X
Windows

Linux

All OS with a Java 7 VM

Linux

Ubuntu

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

close to SQL 92

ANSI SQL for queries (using Apache Calcite)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

YQL, an SQL-based language, is supported

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

4D proprietary IDE
PHP

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

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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 for users and roles

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Access Control Lists

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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