DBMS > Elasticsearch vs. GridDB vs. OpenTSDB vs. Oracle

System Properties Comparison Elasticsearch vs. GridDB vs. OpenTSDB 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

Scalable in-memory time series database optimized for IoT and Big Data

Scalable Time Series DBMS based on HBase

Widely used RDBMS

Primary database model

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Key-value store
Relational 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	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.elastic.co/elasticsearch

griddb.net

opentsdb.net

www.oracle.com/database

Technical documentation

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

docs.griddb.net

opentsdb.net/docs/build/html/index.html

docs.oracle.com/en/database

Developer

Elastic

Toshiba Corporation

currently maintained by Yahoo and other contributors

Oracle

Initial release

2010

2013

2011

1980

Current release

8.6, January 2023

5.1, August 2022

23c, September 2023

License

Commercial or Open Source

Open Source

Elastic License

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

LGPL

commercial

restricted free version is available

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

Java

C++

Java

C and C++

Server operating systems

All OS with a Java VM

Linux

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

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

numeric data for metrics, strings for tags

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
Telnet API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Erlang
Go
Java
Python
R
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

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

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 within container, eventual consistency across containers

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

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 can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.