DBMS > BigchainDB vs. HEAVY.AI vs. KeyDB vs. Microsoft Azure AI Search vs. Oracle

System Properties Comparison BigchainDB vs. HEAVY.AI vs. KeyDB vs. Microsoft Azure AI Search vs. Oracle

Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Search-as-a-service for web and mobile app development

Widely used RDBMS

Primary database model

Secondary database models

Spatial DBMS

Vector DBMS

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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.bigchaindb.com

github.com/heavyai/heavydb
www.heavy.ai

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/en-us/services/search

www.oracle.com/database

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.heavy.ai

docs.keydb.dev

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

Developer

HEAVY.AI, Inc.

EQ Alpha Technology Ltd.

Microsoft

Oracle

Initial release

2016

2019

2015

1980

Current release

5.10, January 2022

23c, September 2023

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD-3

commercial

restricted free version is available

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

Python

C++ and CUDA

C++

C and C++

Server operating systems

Linux

hosted

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

Data scheme

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Proprietary protocol

RESP - REdis Serialization Protoco

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
Java
JavaScript
Python

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

Server-side scripts

Stored procedures

Lua

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

fine grained access rights according to SQL-standard

simple password-based access control and ACL

yes

using Azure authentication

fine grained access rights according to SQL-standard

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