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DBMS > Faircom DB vs. Google Cloud Bigtable vs. Neo4j

Vergleich der Systemeigenschaften Faircom DB vs. Google Cloud Bigtable vs. Neo4j

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Redaktionelle Informationen bereitgestellt von DB-Engines
NameFaircom DB infoformerly c-treeACE  Xaus Vergleich ausschliessenGoogle Cloud Bigtable  Xaus Vergleich ausschliessenNeo4j  Xaus Vergleich ausschliessen
KurzbeschreibungNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primäres DatenbankmodellKey-Value Store
Relational DBMS
Key-Value Store
Wide Column Store
Graph DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte0,17
Rang#351  Overall
#52  Key-Value Stores
#148  Relational DBMS
Punkte5,47
Rang#76  Overall
#10  Key-Value Stores
#7  Wide Column Stores
Punkte55,84
Rang#20  Overall
#1  Graph DBMS
Websitewww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtableneo4j.com
Technische Dokumentationlearn.faircomcorp.com/­developers/­documentation_directorycloud.google.com/­bigtable/­docsneo4j.com/­docs
EntwicklerFairCom CorporationGoogleNeo4j, Inc.
Erscheinungsjahr197920152007
Aktuelle VersionV12, November 20205.3, Dezember 2022
Lizenz infoCommercial or Open Sourcekommerziell infoRestricted, free version availablekommerziellOpen Source infoGPL Version3, kommerzielle Lizenzen verfügbar bei Bedarf
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinjanein
DBaaS Angebote (gesponserte Links) infoDatabase 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.
ImplementierungsspracheANSI C, C++Java, Scala
Server BetriebssystemeAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
gehostetLinux infoKann auch Server-los als embedded Java Datenbank verwendet werden.
OS X
Solaris
Windows
Datenschemaschema free, schema optional, schema required, partial schema,schemafreischemafrei und schema-optional
Typisierung infovordefinierte Datentypen, z.B. float oder dateja, ANSI Standard SQL Types, JSON, typed binary structuresneinja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinnein
Sekundärindizesjaneinja infoAustauschbares Index Subsystem, per Default Apache Lucene
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsneinnein
APIs und andere ZugriffskonzepteADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Unterstützte Programmiersprachen.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-seitige Scripts infoStored Proceduresja info.Net, JavaScript, C/C++neinja infoUser defined Procedures and Functions
Triggersjaneinja infomittels Event Handler
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingja, mit Neo4j Fabric
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zonesCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoBietet ein API für Map/Reduce Operationenneinjanein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Fremdschlüssel inforeferenzielle Integritätjaneinja infoBeziehungen in Graphen
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren Datenmanipulationentunable from ACID to Eventually ConsistentAtomic single-row operationsACID
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajaja
Durability infoDauerhafte Speicherung der DatenYes, tunable from durable to delayed durability to in-memoryjaja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjanein
Berechtigungskonzept infoZugriffskontrolleFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
Weitere Informationen bereitgestellt vom Systemhersteller
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableNeo4j
Specific characteristicsAchieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» mehr
Neo4j delivers graph technology that has been battle tested for performance and scale...
» mehr
Competitive advantagesTop Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» mehr
Neo4j is the market leader, graph database category creator, and the most widely...
» mehr
Typical application scenariosReal-time transaction processing solutions leverage FairCom DB because its NoSQL...
» mehr
Real-Time Recommendations Master Data Management Identity and Access Management Network...
» mehr
Key customersMicrosoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» mehr
Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» mehr
Market metricsFrom banking and financial transactions, transportation, warehouse automation, package...
» mehr
Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» mehr
Licensing and pricing modelsJust as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» mehr
GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» mehr
Neuigkeiten

This Week in Neo4j: VS Code Extension, Geospatial Data, Closeness Centrality, Project Management, and More!
28. Januar 2023

How to Graph an ERP System in 3 Easy Steps
26. Januar 2023

Graph Analytics: The Future in Data Science?
25. Januar 2023

This Week in Neo4j: OpenAI, Deploying on GCP, Neodash, Graph Algorithms, Python, and More
21. Januar 2023

Enabling Low/No Code Engineering Experience and Operationalizing Information Models
20. Januar 2023

Wir laden Vertreter der Systemhersteller ein uns zu kontaktieren, um die Systeminformationen zu aktualisieren und zu ergänzen,
sowie um Herstellerinformationen wie Schlüsselkunden, Vorteile gegenüber Konkurrenten und Marktmetriken anzuzeigen.

Zugehörige Produkte und Dienstleistungen
DrittanbieterGraphable delivers expert services for Neo4j and other Graph DBMS.
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Weitere Ressourcen
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableNeo4j
DB-Engines Blog Posts

Applying Graph Analytics to Game of Thrones
12. Juni 2019, Amy Hodler & Mark Needham, Neo4j (guest author)

MySQL, PostgreSQL and Redis are the winners of the March ranking
2. März 2016, Paul Andlinger

The openCypher Project: Help Shape the SQL for Graphs
22. Dezember 2015, Emil Eifrem (guest author)

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