DBMS > BigchainDB vs. GridGain vs. Heroic vs. Oracle vs. RethinkDB

System Properties Comparison BigchainDB vs. GridGain vs. Heroic vs. Oracle vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Widely used RDBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store

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

Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

www.bigchaindb.com

www.gridgain.com

github.com/spotify/heroic

www.oracle.com/database

rethinkdb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.gridgain.com/docs/index.html

spotify.github.io/heroic

docs.oracle.com/en/database

rethinkdb.com/docs

Developer

GridGain Systems, Inc.

Spotify

Oracle

The Linux Foundation

since July 2017

Initial release

2016

2007

2014

1980

2009

Current release

GridGain 8.5.1

23c, September 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2

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

Python

Java, C++, .Net

Java

C and C++

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

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

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

via Elasticsearch

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

PL/SQL

also stored procedures in Java possible

Triggers

yes (cache interceptors and events)

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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'

User concepts

Access control

yes

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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