DBMS > BigchainDB vs. EJDB vs. HBase vs. Oracle vs. SwayDB

System Properties Comparison BigchainDB vs. EJDB vs. HBase vs. Oracle vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Widely used RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.bigchaindb.com

github.com/Softmotions/ejdb

hbase.apache.org

www.oracle.com/database

swaydb.simer.au

Technical documentation

bigchaindb.readthedocs.io/en/latest

github.com/Softmotions/ejdb/blob/master/README.md

hbase.apache.org/book.html

docs.oracle.com/en/database

Developer

Softmotions

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

Simer Plaha

Initial release

2016

2012

2008

1980

2018

Current release

2.3.4, January 2021

23c, September 2023

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

GPLv2

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Java

C and C++

Scala

Server operating systems

Linux

server-less

Linux
Unix
Windows

using Cygwin

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

schema-free, schema definition possible

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

options to bring your own types, AVRO

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

in-process shared library

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

isolation level can be parameterized

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

yes

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

fine grained access rights according to SQL-standard

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