DBMS > Elasticsearch vs. Google Cloud Datastore vs. Infobright vs. Oracle

System Properties Comparison Elasticsearch vs. Google Cloud Datastore vs. Infobright vs. Oracle

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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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Widely used RDBMS

Primary database model

Search engine

Document store

Relational 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	135.35
Rank	#7	Overall
	#1	Search engines

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.elastic.co/elasticsearch

cloud.google.com/datastore

ignitetech.com/softwarelibrary/infobrightdb

www.oracle.com/database

Technical documentation

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

cloud.google.com/datastore/docs

docs.oracle.com/en/database

Developer

Elastic

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

Initial release

2010

2008

2005

1980

Current release

8.6, January 2023

23c, September 2023

License

Commercial or Open Source

Open Source

Elastic License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java

C and C++

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

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

Data scheme

schema-free

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

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

yes, details here

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (GQL)

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

yes

using Google App Engine

PL/SQL

also stored procedures in Java possible

Triggers

yes

by using the 'percolation' feature

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

using Google Cloud Dataflow

can be realized in PL/SQL

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 or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

isolation level can be parameterized

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 for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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