DBMS > 4D vs. GigaSpaces vs. Tarantool vs. Yanza

System Properties Comparison 4D vs. GigaSpaces vs. Tarantool vs. Yanza

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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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

with Tarantool/GIS extension

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

www.4d.com

www.gigaspaces.com

www.tarantool.io

yanza.com

Technical documentation

developer.4d.com

docs.gigaspaces.com/latest/landing.html

www.tarantool.io/en/doc

Developer

4D, Inc

Gigaspaces Technologies

Yanza

Initial release

1984

2000

2008

2015

Current release

v20, April 2023

15.5, September 2020

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

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

commercial

free version available

Cloud-based only

Only available as a cloud service

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

Java, C++, .Net

C and C++

Server operating systems

OS X
Windows

Linux
macOS
Solaris
Windows

BSD
Linux
macOS

Windows

Data scheme

yes

schema-free

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

schema-free

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 can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-99 for query and DML statements

Full-featured ANSI SQL support

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Open binary protocol

HTTP API

Supported programming languages

4D proprietary IDE
PHP

.Net
C++
Java
Python
Scala

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

Triggers

yes

yes, event driven architecture

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

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

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

Users and groups

Role-based access control

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

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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