DBMS > HBase vs. InfinityDB vs. Oracle NoSQL vs. SQLite

System Properties Comparison HBase vs. InfinityDB vs. Oracle NoSQL vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

A Java embedded Key-Value Store which extends the Java Map interface

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Widely used embeddable, in-process RDBMS

Primary database model

Wide column store

Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

hbase.apache.org

boilerbay.com

www.oracle.com/database/nosql/technologies/nosql

www.sqlite.org

Technical documentation

hbase.apache.org/book.html

boilerbay.com/infinitydb/manual

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Boiler Bay Inc.

Oracle

Dwayne Richard Hipp

Initial release

2008

2002

2011

2000

Current release

2.3.4, January 2021

4.0

24.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

Linux
Solaris SPARC/x86

server-less

Data scheme

schema-free, schema definition possible

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

dynamic column types

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

optional

yes

not rigid because of 'dynamic typing' concept.

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Optimistic locking for transactions; no isolation for bulk loads

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

off heap cache

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users and roles

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