DBMS > Heroic vs. IBM Cloudant vs. Oracle Coherence vs. RocksDB vs. Warp 10

System Properties Comparison Heroic vs. IBM Cloudant vs. Oracle Coherence vs. RocksDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

Oracles in-memory data grid solution

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.oracle.com/java/coherence

rocksdb.org

www.warp10.io

Technical documentation

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

docs.oracle.com/en/middleware/standalone/coherence

github.com/facebook/rocksdb/wiki

www.warp10.io/content/02_Getting_started

Developer

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

Facebook, Inc.

SenX

Initial release

2014

2010

2007

2013

2015

Current release

14.1, August 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

Java

C++

Java

Server operating systems

hosted

All OS with a Java VM

Linux

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

APIs and other access methods

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

RESTful HTTP/JSON API

JCache
JPA
RESTful HTTP API

C++ API
Java API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

WarpScript

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

yes

selectable replication factor

based on HBase

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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

configurable

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

optionally

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

Access rights for users can be defined per database

authentification to access the cache via certificates or http basic authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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