DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. PostgreSQL vs. Spark SQL
System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. PostgreSQL vs. Spark SQL
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Name | Amazon DocumentDB Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Microsoft SQL Server Xexclude from comparison | PostgreSQL Xexclude from comparison | Spark SQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, scalable, highly available, and fully managed MongoDB-compatible database service | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Microsofts flagship relational DBMS | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Spark SQL is a component on top of 'Spark Core' for structured data processing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Key-value store Wide column store | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/documentdb | cloud.google.com/bigtable | www.microsoft.com/en-us/sql-server | www.postgresql.org | spark.apache.org/sql | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/documentdb/resources | cloud.google.com/bigtable/docs | learn.microsoft.com/en-US/sql/sql-server | www.postgresql.org/docs | spark.apache.org/docs/latest/sql-programming-guide.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2019 | 2015 | 1989 | 1989 1989: Postgres, 1996: PostgreSQL | 2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | SQL Server 2022, November 2022 | 16.2, February 2024 | 3.5.0 ( 2.13), September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | commercial restricted free version is available | Open Source BSD | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C | Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | hosted | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | yes | yes | 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. | no | no | yes | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | no | yes | yes standard with numerous extensions | SQL-like DML and DDL statements | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | proprietary protocol using JSON (MongoDB compatible) | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | ADO.NET JDBC ODBC OLE DB Tabular Data Stream (TDS) | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Go Java JavaScript (Node.js) PHP Python | C# C++ Go Java JavaScript (Node.js) Python | C# C++ Delphi Go Java JavaScript (Node.js) PHP Python R Ruby Visual Basic | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Java Python R Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding | tables can be distributed across several files (horizontal partitioning); sharding through federation | partitioning by range, list and (since PostgreSQL 11) by hash | yes, utilizing Spark Core | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas | Internal replication in Colossus, and regional replication between two clusters in different zones | yes, but depending on the SQL-Server Edition | Source-replica replication other methods possible by using 3rd party extensions | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no typically not used, however similar functionality with DBRef possible | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic single-document operations | Atomic single-row operations | ACID | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon DocumentDB | Google Cloud Bigtable | Microsoft SQL Server | PostgreSQL | Spark SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Microsoft SQL Server is the DBMS of the Year | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services Run complex queries on massive amounts of data stored on your Amazon DocumentDB clusters using Apache Spark ... Game Developer's Guide to Amazon DocumentDB (with MongoDB compatibility) Part Three: Operation Best Practices ... provided by Google News | Google expands BigQuery with Gemini, brings vector support to cloud databases What is Google Bigtable? | Definition from TechTarget Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable provided by Google News | Provision Premium SSD v2 Storage for Microsoft SQL Server Containerize SQL Server workloads with Amazon EKS and DH2i | Amazon Web Services A tumultuous, titanic Patch Tuesday as Microsoft makes some changes Top 12 Data Migration Tools for 2024 Deploying a highly available Microsoft SQL Server database on Oracle Cloud Infrastructure (OCI) using AlwaysON ... provided by Google News | Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... pgEdge Distributed PostgreSQL Introduces Automatic DDL Replication and Snowflake Sequences for Postgres Breaking Boundaries: PostgreSQL 16 is now available on IBM Cloud PeerDB: PostgreSQL Data Movement Platform Company Closes $3.6 Million Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need provided by Google News | Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services What is Apache Spark? The big data platform that crushed Hadoop Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024 1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services provided by Google News |
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