DBMS > Amazon DynamoDB vs. Google Cloud Bigtable vs. Percona Server for MySQL vs. PostgreSQL vs. RRDtool
System Properties Comparison Amazon DynamoDB vs. Google Cloud Bigtable vs. Percona Server for MySQL vs. PostgreSQL vs. RRDtool
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| Name | Amazon DynamoDB Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Percona Server for MySQL Xexclude from comparison | PostgreSQL Xexclude from comparison | RRDtool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features. | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. The data is stored in a circular buffer, thus the system storage footprint remains constant over time. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value 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. | Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | cloud.google.com/bigtable | www.percona.com/software/mysql-database/percona-server | www.postgresql.org | oss.oetiker.ch/rrdtool | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | cloud.google.com/bigtable/docs | www.percona.com/downloads/Percona-Server-LATEST | www.postgresql.org/docs | oss.oetiker.ch/rrdtool/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Percona | PostgreSQL Global Development Group www.postgresql.org/developer | Tobias Oetiker | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 2015 | 2008 | 1989 1989: Postgres, 1996: PostgreSQL | 1999 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 8.0.36-28, 2024 | 16.3, May 2024 | 1.8.0, 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free tier for a limited amount of database operations | commercial | Open Source GPL version 2 | Open Source BSD | Open Source GPL V2 and FLOSS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C and C++ | C | C Implementations in Java (e.g. RRD4J) and C# available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | hosted | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | HP-UX Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | yes | yes | Numeric data only | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes | yes specific XML-type available, but no XML query functionality. | no Exporting into and restoring from XML files possible | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | no | yes | yes standard with numerous extensions | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | ADO.NET JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | in-process shared library Pipes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | C# C++ Go Java JavaScript (Node.js) Python | Ada C C# C++ D Eiffel Erlang Haskell Java Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C with librrd library C# with a different implementation of RRDToolJava with a different implementation of RRDToolJavaScript (Node.js) with a different implementation of RRDToolLua Perl PHP with a wrapper libraryPython Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | no | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by integration with AWS Lambda | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | none | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes | Internal replication in Colossus, and regional replication between two clusters in different zones | Multi-source replication Source-replica replication XtraDB Cluster | 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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | Immediate Consistency | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID ACID across one or more tables within a single AWS account and region | Atomic single-row operations | ACID | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes by using the rrdcached daemon | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Users with fine-grained authorization concept no user groups or roles | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DynamoDB | Google Cloud Bigtable | Percona Server for MySQL | PostgreSQL | RRDtool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? Monitoring PostgreSQL with Redgate Monitor Freecharge lowered their identity management system cost and improved scaling by switching to Amazon DynamoDB ... Migrating Uber's Ledger Data from DynamoDB to LedgerStore Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Using the circuit-breaker pattern with AWS Lambda extensions and Amazon DynamoDB | Amazon Web Services Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services provided by Google News Google's AI-First Strategy Brings Vector Support To Cloud Databases Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Google introduces Cloud Bigtable managed NoSQL database to process data at scale Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database provided by Google News A Momentous 2023, Headlined by a 19% increase of ARR, Positions Percona for Even Greater Success in the Year ... Update or migrate? Planning for MySQL 5.7 EOL Sizing Up Servers: Intel's Skylake-SP Xeon versus AMD's EPYC 7000 - The Server CPU Battle of the Decade? How to deploy the Percona database performance monitor with Docker ScaleFlux computational storage makes Percona MySQL faster – Blocks and Files provided by Google News Deep PostgreSQL Thoughts: Valuing Currency At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch Nutanix and EDB enhance PostgreSQL for enterprise apps provided by Google News SQLi vulnerability in Cacti could lead to RCE (CVE-2023-51448) Critical IP spoofing bug patched in Cacti How to install Cacti SNMP Monitor on Ubuntu Installation Guide for Collectd and Collectd-Web to Monitor Server Resources in Linux Cacti servers under attack by attackers exploiting CVE-2022-46169 provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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