DBMS > Amazon DocumentDB vs. Apache Impala vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. PostgreSQL
System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. PostgreSQL
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Name | Amazon DocumentDB Xexclude from comparison | Apache Impala Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Microsoft SQL Server Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, scalable, highly available, and fully managed MongoDB-compatible database service | Analytic DBMS for Hadoop | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Relational DBMS | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | 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 | impala.apache.org | cloud.google.com/bigtable | www.microsoft.com/en-us/sql-server | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/documentdb/resources | impala.apache.org/impala-docs.html | cloud.google.com/bigtable/docs | learn.microsoft.com/en-US/sql/sql-server | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation Apache top-level project, originally developed by Cloudera | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2019 | 2013 | 2015 | 1989 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 4.1.0, June 2022 | SQL Server 2022, November 2022 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache Version 2 | commercial | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux | hosted | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | no | 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 | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like DML and DDL statements | no | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | proprietary protocol using JSON (MongoDB compatible) | JDBC ODBC | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Go Java JavaScript (Node.js) PHP Python | All languages supporting JDBC/ODBC | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes user defined functions and integration of map-reduce | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding | Sharding | tables can be distributed across several files (horizontal partitioning); sharding through federation | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas | selectable replication factor | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | yes query execution via MapReduce | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual 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 | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic single-document operations | no | Atomic single-row operations | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles | Access rights for users, groups and roles based on Apache Sentry and Kerberos | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon DocumentDB | Apache Impala | Google Cloud Bigtable | Microsoft SQL Server | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Monitoring PostgreSQL with Redgate Monitor Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services AWS announces Amazon DocumentDB I/O-Optimized Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services AWS announces vector search for Amazon DocumentDB Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services provided by Google News Cloudera creates observability tool to help enterprises manage cloud costs Apache Impala 4 Supports Operator Multi-Threading Apache Impala becomes Top-Level Project Cloudera Bringing Impala to AWS Cloud Apache Doris just 'graduated': Why care about this SQL data warehouse provided by Google News Google's AI-First Strategy Brings Vector Support To Cloud Databases What is Google Bigtable? | Definition from TechTarget Google announces Axion, its first Arm-based CPU for data centers Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Review: Google Bigtable scales with ease provided by Google News Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers RDS Custom for SQL Server supports SQL Server Developer Edition How to Know When It's Time for a Microsoft SQL Server Upgrade Top 35 SQL Server Interview Questions And Answers for 2024 Deploying a highly available Microsoft SQL Server database on Oracle Cloud Infrastructure (OCI) using AlwaysON ... provided by Google News Automatically Generate Types for Your PostgreSQL Database Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Oracle Introduces PostgreSQL Running Native on OCI Your MySQL 5.7 and PostgreSQL 11 databases will be automatically enrolled into Amazon RDS Extended Support ... provided by Google News |
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