DBMS > atoti vs. HEAVY.AI vs. IBM Db2 vs. Lovefield vs. Yanza

System Properties Comparison atoti vs. HEAVY.AI vs. IBM Db2 vs. Lovefield vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Common in IBM host environments, 2 different versions for host and Windows/Linux

Embeddable relational database for web apps written in pure JavaScript

Time Series DBMS for IoT Applications

Primary database model

Object oriented DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

atoti.io

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/db2

google.github.io/lovefield

yanza.com

Technical documentation

docs.atoti.io

docs.heavy.ai

www.ibm.com/docs/en/db2

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

ActiveViam

HEAVY.AI, Inc.

IBM

Google

Yanza

Initial release

2016

1983

host version

2014

2015

Current release

5.10, January 2022

12.1, October 2016

2.1.12, February 2017

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; enterprise edition available

commercial

free version is available

Open Source

Apache 2.0

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++ and CUDA

C and C++

JavaScript

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

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

tested with Chrome, Firefox, IE, Safari

Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript

any language that supports HTTP calls

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Using read-only observers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Round robin

Sharding

only with Windows/Unix/Linux Version

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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