DBMS > Elasticsearch vs. Microsoft Azure Table Storage vs. Oracle vs. OrientDB vs. TigerGraph

System Properties Comparison Elasticsearch vs. Microsoft Azure Table Storage vs. Oracle vs. OrientDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Search engine

Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store

Graph DBMS

Secondary database models

Document store
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	128.79
Rank	#8	Overall
	#1	Search engines

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

www.elastic.co/elasticsearch

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database

orientdb.org

www.tigergraph.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.oracle.com/en/database

www.orientdb.com/docs/last/index.html

docs.tigergraph.com

Developer

Elastic

Microsoft

Oracle

OrientDB LTD; CallidusCloud; SAP

Initial release

2010

2012

1980

2010

2017

Current release

8.6, January 2023

23c, September 2023

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Elastic License

commercial

restricted free version is available

Open Source

Apache version 2

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 and C++

Java

C++

Server operating systems

All OS with a Java VM

hosted

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

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language, no joins

SQL-like query language (GSQL)

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Java

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Java, Javascript

yes

Triggers

yes

by using the 'percolation' feature

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

can be realized in PL/SQL

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Relationships in graphs

Transaction concepts

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

optimistic locking

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

Memcached and Redis integration

yes

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

User concepts

Access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Role-based access control

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