DBMS > Amazon Neptune vs. HBase vs. Microsoft Access vs. Oracle vs. TigerGraph

System Properties Comparison Amazon Neptune vs. HBase vs. Microsoft Access vs. Oracle vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/neptune

hbase.apache.org

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database

www.tigergraph.com

Technical documentation

aws.amazon.com/neptune/developer-resources

hbase.apache.org/book.html

developer.microsoft.com/en-us/access

docs.oracle.com/en/database

docs.tigergraph.com

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Oracle

Initial release

2017

2008

1992

1980

2017

Current release

2.3.4, January 2021

1902 (16.0.11328.20222), March 2019

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

commercial

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

Java

C++

C and C++

C++

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Windows

Not a real database server, but making use of DLLs

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

Linux

Data scheme

schema-free

schema-free, schema definition possible

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

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

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java API
RESTful HTTP API
Thrift

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

C++
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

since Access 2010 using the ACE-engine

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

but no files for transaction logging

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

but no files for transaction logging

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

Role-based access control

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