DBMS > Cachelot.io vs. Google Cloud Datastore vs. RavenDB vs. Riak TS vs. ToroDB

System Properties Comparison Cachelot.io vs. Google Cloud Datastore vs. RavenDB vs. Riak TS vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Open Source Operational and Transactional Enterprise NoSQL Document Database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

cachelot.io

cloud.google.com/datastore

ravendb.net

github.com/torodb/server

Technical documentation

cloud.google.com/datastore/docs

ravendb.net/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Google

Hibernating Rhinos

Open Source, formerly Basho Technologies

8Kdata

Initial release

2015

2008

2010

2015

2016

Current release

5.4, July 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

AGPL version 3, commercial license available

Open Source

AGPL-V3

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

C++

Erlang

Java

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

All OS with a Java 7 VM

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, details here

yes

string, integer, double, boolean, date, object_id

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

restricted

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language (RQL)

yes, limited

APIs and other access methods

Memcached protocol

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

using Google App Engine

yes

Erlang

Triggers

Callbacks using the Google Apps Engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

Multi-source replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

links between datasets can be stored

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID, Cluster-wide transaction available

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

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

Authorization levels configured per client per database

Access rights for users and roles

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