DBMS > 4D vs. LeanXcale vs. Memcached vs. Vertica vs. Yanza

System Properties Comparison 4D vs. LeanXcale vs. Memcached vs. Vertica vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Application development environment with integrated database management system

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

In-memory key-value store, originally intended for caching

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.

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Column oriented

Time Series DBMS

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	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

yanza.com

Technical documentation

developer.4d.com

github.com/memcached/memcached/wiki

vertica.com/documentation

Developer

4D, Inc

LeanXcale

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

OpenText

previously Micro Focus and Hewlett Packard

Yanza

Initial release

1984

2015

2003

2005

2015

Current release

v20, April 2023

1.6.25, March 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Limited community edition free

commercial

free version available

Cloud-based only

Only available as a cloud service

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

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux

Windows

Data scheme

yes

schema-free

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

schema-free

Typing

predefined data types such as float or date

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

yes

through Apache Derby

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

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Proprietary protocol

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

character-based, interactive, front-end utility

HTTP API

Supported programming languages

4D proprietary IDE
PHP

C
Java
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

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.

yes

User concepts

Access control

Users and groups

yes

using SASL (Simple Authentication and Security Layer) protocol

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

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

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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