DBMS > Ehcache vs. Google Cloud Bigtable vs. Heroic vs. RethinkDB vs. SwayDB

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. Heroic vs. RethinkDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store

Key-value store
Wide column store

Time Series DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.ehcache.org

cloud.google.com/bigtable

github.com/spotify/heroic

rethinkdb.com

swaydb.simer.au

Technical documentation

www.ehcache.org/documentation

cloud.google.com/bigtable/docs

spotify.github.io/heroic

rethinkdb.com/docs

Developer

Terracotta Inc, owned by Software AG

Google

Spotify

The Linux Foundation

since July 2017

Simer Plaha

Initial release

2009

2015

2014

2009

2018

Current release

3.10.0, March 2022

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

JCache

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

Supported programming languages

Java

C#
C++
Go
Java
JavaScript (Node.js)
Python

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

yes

Cache Event Listeners

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Atomic single-row operations

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

users and table-level permissions

More information provided by the system vendor

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