DBMS > atoti vs. Heroic vs. Kyligence Enterprise vs. TimesTen

System Properties Comparison atoti vs. Heroic vs. Kyligence Enterprise vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A distributed analytics engine for big data, built on top of Apache Kylin

In-Memory RDBMS compatible to Oracle

Primary database model

Object oriented DBMS

Time Series DBMS

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

atoti.io

github.com/spotify/heroic

kyligence.io/kyligence-enterprise

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

Technical documentation

docs.atoti.io

spotify.github.io/heroic

docs.oracle.com/database/timesten-18.1

Developer

ActiveViam

Spotify

Kyligence, Inc.

Oracle, TimesTen Performance Software, HP

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

Initial release

2014

2016

1998

Current release

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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

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

Data scheme

schema-free

yes

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

via Elasticsearch

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Python

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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