DBMS > BoltDB vs. Google BigQuery vs. Hive vs. Oracle Rdb vs. RocksDB

System Properties Comparison BoltDB vs. Google BigQuery vs. Hive vs. Oracle Rdb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Large scale data warehouse service with append-only tables

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

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

Primary database model

Key-value store

Relational DBMS

Key-value store

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

cloud.google.com/bigquery

hive.apache.org

www.oracle.com/database/technologies/related/rdb.html

rocksdb.org

Technical documentation

cloud.google.com/bigquery/docs

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

www.oracle.com/database/technologies/related/rdb-doc.html

github.com/facebook/rocksdb/wiki

Developer

Google

Apache Software Foundation

initially developed by Facebook

Oracle, originally developed by Digital Equipment Corporation (DEC)

Facebook, Inc.

Initial release

2013

2010

2012

1984

2013

Current release

3.1.3, April 2022

7.4.1.1, 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache Version 2

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

HP Open VMS

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

C++ API
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

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

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

yes, on a single node

yes

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.

yes

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

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