DBMS > GridDB vs. Manticore Search vs. Neo4j vs. Oracle

System Properties Comparison GridDB vs. Manticore Search vs. Neo4j vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

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

Multi-storage database for search, including full-text search.

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Widely used RDBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

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	2.02
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Website

griddb.net

manticoresearch.com

neo4j.com

www.oracle.com/database

Technical documentation

docs.griddb.net

manual.manticoresearch.com

neo4j.com/docs

docs.oracle.com/en/database

Developer

Toshiba Corporation

Manticore Software

Neo4j, Inc.

Oracle

Initial release

2013

2017

2007

1980

Current release

5.1, August 2022

6.0, February 2023

5.19, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

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

Open Source

GPL version 2

Open Source

GPL version3, commercial licenses available

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

Java, Scala

C and C++

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

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

Data scheme

yes

Fixed schema

schema-free and schema-optional

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

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

user defined functions

yes

User defined Procedures and Functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes using Neo4j Fabric

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication based on Galera library

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate consistency within container, eventual consistency across containers

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID at container level

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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 can be defined per database

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

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

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

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

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

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

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

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

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

GitHub trending repository
» more

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

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

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

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