DBMS > Cachelot.io vs. Google BigQuery vs. Rockset vs. SWC-DB vs. Yanza

System Properties Comparison Cachelot.io vs. Google BigQuery vs. Rockset vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

Large scale data warehouse service with append-only tables

A scalable, reliable search and analytics service in the cloud, built on RocksDB

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Relational DBMS
Search engine

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cachelot.io

cloud.google.com/bigquery

rockset.com

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

cloud.google.com/bigquery/docs

docs.rockset.com

Developer

Google

Rockset

Alex Kashirin

Yanza

Initial release

2015

2010

2019

2020

2015

Current release

0.5, April 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

all fields are automatically indexed

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

SQL-like query language

APIs and other access methods

Memcached protocol

RESTful HTTP/JSON API

HTTP REST

Proprietary protocol
Thrift

HTTP API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and organizations can be defined via Rockset console

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