DBMS > Amazon DynamoDB vs. Faircom DB vs. Google Cloud Bigtable vs. PostgreSQL vs. Solr
Vergleich der Systemeigenschaften Amazon DynamoDB vs. Faircom DB vs. Google Cloud Bigtable vs. PostgreSQL vs. Solr
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Name | Amazon DynamoDB Xaus Vergleich ausschliessen | Faircom DB formerly c-treeACE Xaus Vergleich ausschliessen | Google Cloud Bigtable Xaus Vergleich ausschliessen | PostgreSQL Xaus Vergleich ausschliessen | Solr Xaus Vergleich ausschliessen | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Gehostetes, skalierbares Datenbankservice von Amazon; die Daten werden in der Amazon Cloud gespeichert | Native 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. | Weit verbreitetes, allgemein einsetzbares Open Source RDBMS Entwickelt als objektorientiertes DBMS, im Laufe der Zeit um 'Standards' wie SQL erweitert | Eine häufig verwendete Suchmaschinentechnologie basierend auf Apache Lucene | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primäres Datenbankmodell | Document Store Key-Value Store | Key-Value Store Relational DBMS | Key-Value Store Wide Column Store | Relational DBMS mit objektorientierten Erweiterungen, z.B.: benutzerdefinierte Datentypen/Funktionen und Vererbung. Key/Value handling mit hstore Modul. | Suchmaschine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Sekundäre Datenbankmodelle | Document Store Graph DBMS with Apache Age Spatial DBMS Vektor DBMS with pgvector extension | Spatial DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/dynamodb | www.faircom.com/products/faircom-db | cloud.google.com/bigtable | www.postgresql.org | solr.apache.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technische Dokumentation | docs.aws.amazon.com/dynamodb | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | cloud.google.com/bigtable/docs | www.postgresql.org/docs | solr.apache.org/resources.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Entwickler | Amazon | FairCom Corporation | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Erscheinungsjahr | 2012 | 1979 | 2015 | 1989 1989: Postgres, 1996: PostgreSQL | 2006 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Aktuelle Version | V12, November 2020 | 16.3, Mai 2024 | 9.6.0, April 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lizenz Commercial or Open Source | kommerziell kostenlos bis zu einer gewissen Anzahl von Datenbankoperationen | kommerziell Restricted, free version available | kommerziell | Open Source BSD | Open Source Apache Version 2 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Ausschließlich ein Cloud-Service Nur als Cloud-Service verfügbar | ja | nein | ja | nein | nein | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS Angebote (gesponserte Links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementierungssprache | ANSI C, C++ | C | Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server Betriebssysteme | gehostet | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | gehostet | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Alle Betriebssysteme mit einer Java VM Läuft als Servlet in einem Servlet Container (z.B. Tomcat, Jetty ist inkludiert) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Datenschema | schemafrei | schema free, schema optional, schema required, partial schema, | schemafrei | ja | ja Dynamic Fields enables on-the-fly addition of new fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typisierung vordefinierte Datentypen, z.B. float oder date | ja | ja, ANSI Standard SQL Types, JSON, typed binary structures | nein | ja | ja mit benutzerdefinierten Datentypen und automatic typing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML Unterstützung Verarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLT | nein | nein | ja specific XML-type available, but no XML query functionality. | ja | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Sekundärindizes | ja | ja | nein | ja | ja Alle Suchfelder werden automatisch indiziert | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | nein | yes, ANSI SQL with proprietary extensions | nein | ja Standard mit zahlreichen Erweiterungen | Solr Parallel SQL Interface | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs und andere Zugriffskonzepte | RESTful HTTP API | ADO.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) | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API RESTful HTTP/JSON API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unterstützte Programmiersprachen | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | C# C++ Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | .Net Erlang Java JavaScript jede Sprache, die Sockets und entweder XML oder JSON unterstützt Perl PHP Python Ruby Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-seitige Scripts Stored Procedures | nein | ja .Net, JavaScript, C/C++ | nein | benutzerdefinierte Funktionen realisiert z.B. mit spezifischer Sprache PL/pgSQL, aber auch andere Sprachen möglich (Perl, Python, Tcl, etc.) | Java plugins | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | ja by integration with AWS Lambda | ja | nein | ja | ja User configurable commands triggered on index changes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitionierungsmechanismen Methoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen Knoten | Sharding | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replikationsmechanismen Methoden zum redundanten Speichern von Daten auf mehreren Knoten | ja | yes, 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 zones | Source-Replica Replikation andere Varianten durch Verwendung von 3rd party - tools | ja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Bietet ein API für Map/Reduce Operationen | nein kann über Amazon Elastic MapReduce (Amazon EMR) realisiert werden | nein | ja | nein | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Konsistenzkonzept Methoden zur Sicherstellung der Konsistenz in einem verteilten System | Eventual Consistency Immediate Consistency kann bei LeseOperationen spezifiziert werden | Eventual 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) | Immediate Consistency | Eventual Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Fremdschlüssel referenzielle Integrität | nein | ja | nein | ja | nein | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaktionskonzept Unterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren Datenmanipulationen | ACID ACID across one or more tables within a single AWS account and region | tunable from ACID to Eventually Consistent | Atomic single-row operations | ACID | optimistic Locking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Unterstützung von gleichzeitig ausgeführten Datenmanipulationen | ja | ja | ja | ja | ja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Dauerhafte Speicherung der Daten | ja | Yes, tunable from durable to delayed durability to in-memory | ja | ja | ja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-Memory Unterstützung Gibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu halten | ja | nein | nein | ja | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Berechtigungskonzept Zugriffskontrolle | Zugriffsrechte für Benutzer und Rollen über AWS Identity and Access Management (IAM) definierbar | Fine grained access rights according to SQL-standard with additional protections for files | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Benutzer mit feingranularem Berechtigungskonzept entsprechend SQL-Standard | ja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon DynamoDB | Faircom DB formerly c-treeACE | Google Cloud Bigtable | PostgreSQL | Solr | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines Blog Posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Increased popularity for consuming DBMS services out of the cloud | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines Monitoring PostgreSQL with Redgate Monitor How Heroku reduced their operational overhead by migrating their 30 TB self-managed database from Amazon EC2 to ... Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Migrating Uber's Ledger Data from DynamoDB to LedgerStore A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services Distributed Transactions at Scale in Amazon DynamoDB bereitgestellt von Google News FairCom kicks off new era of database technology USA - English bereitgestellt von Google News Google's AI-First Strategy Brings Vector Support To Cloud Databases Google expands BigQuery with Gemini, brings vector support to cloud databases Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease bereitgestellt von Google News ServiceNow trades MariaDB for RaptorDB (PostgreSQL) AGEDB Technology Launches PGTS - PostgreSQL Tech-Support First Principles: Optimizing PostgreSQL for the cloud General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates Automatically Generate Types for Your PostgreSQL Database bereitgestellt von Google News SOLR hosts May Day amid ongoing contract negotiations (SOLR) Technical Pivots with Risk Controls SOLR-led walkout demands better conditions for Compass workers Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ... Top 5 stock gainers and losers: SOLR.V, GRSL.V, ANON.C bereitgestellt von Google News |
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