DBMS > Cachelot.io vs. Heroic vs. searchxml

System Properties Comparison Cachelot.io vs. Heroic vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Time Series DBMS

Native XML DBMS
Search engine

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

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

cachelot.io

github.com/spotify/heroic

www.searchxml.net/category/products

Technical documentation

spotify.github.io/heroic

www.searchxml.net/support/handouts

Developer

Spotify

informationpartners gmbh

Initial release

2015

2014

2015

Current release

1.0

License

Commercial or Open Source

Open Source

Simplified BSD License

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

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Windows

Data scheme

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

via Elasticsearch

yes

SQL

Support of SQL

APIs and other access methods

Memcached protocol

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

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.

User concepts

Access control

Domain, group and role-based access control at the document level and for application services

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