DBMS > Google BigQuery vs. Interbase vs. InterSystems Caché vs. RRDtool

System Properties Comparison Google BigQuery vs. Interbase vs. InterSystems Caché vs. RRDtool

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Light-weight proven RDBMS

originally from Borland

A multi-model DBMS and application server

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

cloud.google.com/bigquery

www.embarcadero.com/products/interbase

www.intersystems.com/products/cache

oss.oetiker.ch/rrdtool

Technical documentation

cloud.google.com/bigquery/docs

docs.embarcadero.com/products/interbase

docs.intersystems.com

oss.oetiker.ch/rrdtool/doc

Developer

Google

Embarcadero

InterSystems

Tobias Oetiker

Initial release

2010

1984

1997

1999

Current release

InterBase 2020, December 2019

2018.1.4, May 2020

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

HP-UX
Linux

Data scheme

yes

depending on used data model

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

export as XML data possible

yes

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C#
C++
Java

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

by using the rrdcached daemon

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.

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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