DBMS > Apache Druid vs. atoti vs. InfinityDB vs. TimesTen vs. Yanza

System Properties Comparison Apache Druid vs. atoti vs. InfinityDB vs. TimesTen vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A Java embedded Key-Value Store which extends the Java Map interface

In-Memory RDBMS compatible to Oracle

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

druid.apache.org

atoti.io

boilerbay.com

www.oracle.com/database/technologies/related/timesten.html

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

docs.atoti.io

boilerbay.com/infinitydb/manual

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation and contributors

ActiveViam

Boiler Bay Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Yanza

Initial release

2012

2002

1998

2015

Current release

29.0.1, April 2024

4.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free versions available

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

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Windows

Data scheme

yes

schema-less columns are supported

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL for querying

Multidimensional Expressions (MDX)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C
C++
Java
PL/SQL

any language that supports HTTP calls

Server-side scripts

Stored procedures

Python

PL/SQL

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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