DBMS > Google BigQuery vs. Interbase vs. OrientDB vs. RocksDB

System Properties Comparison Google BigQuery vs. Interbase vs. OrientDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Light-weight proven RDBMS

originally from Borland

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Key-value store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

cloud.google.com/bigquery

www.embarcadero.com/products/interbase

orientdb.org

rocksdb.org

Technical documentation

cloud.google.com/bigquery/docs

docs.embarcadero.com/products/interbase

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

Developer

Google

Embarcadero

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Initial release

2010

1984

2010

2013

Current release

InterBase 2020, December 2019

3.2.29, March 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSD

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++

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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.

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 and roles; record level security configurable

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