DBMS > Google BigQuery vs. Hive vs. Interbase vs. NSDb vs. NuoDB

System Properties Comparison Google BigQuery vs. Hive vs. Interbase vs. NSDb vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Light-weight proven RDBMS

originally from Borland

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

cloud.google.com/bigquery

hive.apache.org

www.embarcadero.com/products/interbase

nsdb.io

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

docs.embarcadero.com/products/interbase

nsdb.io/Architecture

doc.nuodb.com

Developer

Google

Apache Software Foundation

initially developed by Facebook

Embarcadero

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2010

2012

1984

2017

2013

Current release

3.1.3, April 2022

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2.0

commercial

limited edition free

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

Java, Scala

C++

Server operating systems

hosted

All OS with a Java VM

Android
iOS
Linux
OS X
Windows

Linux
macOS

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

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

Java
Scala

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

yes

Interbase procedure and trigger language

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Interbase Change Views

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

MVCC

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

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, groups and roles

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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