DBMS > Amazon SimpleDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. PostgreSQL vs. Sphinx
System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. PostgreSQL vs. Sphinx
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Name | Amazon SimpleDB Xexclude from comparison | Apache IoTDB Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | PostgreSQL Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Hosted simple database service by Amazon, with the data stored in the Amazon Cloud. There is an unrelated product called SimpleDB developed by Edward Sciore | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store | Time Series DBMS | Key-value store Wide column store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/simpledb | iotdb.apache.org | cloud.google.com/bigtable | www.postgresql.org | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/simpledb | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | cloud.google.com/bigtable/docs | www.postgresql.org/docs | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Apache Software Foundation | PostgreSQL Global Development Group www.postgresql.org/developer | Sphinx Technologies Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2007 | 2018 | 2015 | 1989 1989: Postgres, 1996: PostgreSQL | 2001 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.1.0, April 2023 | 16.3, May 2024 | 3.5.1, February 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache Version 2.0 | commercial | Open Source BSD | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | All OS with a Java VM (>= 1.8) | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes All columns are indexed automatically | yes | no | yes | yes full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like query language | no | yes standard with numerous extensions | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API | JDBC Native API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | ADO.NET JDBC native C library ODBC streaming API for large objects | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C++ Erlang Java PHP Python Ruby Scala | C C# C++ Go Java Python Scala | C# C++ Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none Sharding must be implemented in the application | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | Internal replication in Colossus, and regional replication between two clusters in different zones | Source-replica replication other methods possible by using 3rd party extensions | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Integration with Hadoop and Spark | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Eventual Consistency Strong Consistency with Raft | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Concurrent data updates can be detected by the application | no | Atomic single-row operations | 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 The original contents of fields are not stored in the Sphinx index. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | yes | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon SimpleDB | Apache IoTDB | Google Cloud Bigtable | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | The popularity of cloud-based DBMSs has increased tenfold in four years Amazon - the rising star in the DBMS market | 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 | The DB-Engines ranking includes now search engines A Place for Everything – Amazon SimpleDB Amazon DynamoDB Serves Trillions Of Requests Per Month While Counterpart SimpleDB Is No Longer A Listed ... New SimpleDB Goodies: Enhanced Select, Larger Result Sets, Mandatory HTTPS | Amazon Web Services An Overview of Amazon Web Services - Cloud Application Architectures [Book] Amazon Goes Back to the Future With 'NoSQL' Database provided by Google News TsFile: A Standard Format for IoT Time Series Data Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review Apache Promotes IoT Database Project Timecho Raises Over US$10M in First Funding provided by Google News Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Review: Google Bigtable scales with ease Google scales up Cloud Bigtable NoSQL database Google Cloud makes it cheaper to run smaller workloads on Bigtable Google introduces Cloud Bigtable managed NoSQL database to process data at scale provided by Google News How to implement a better like, views, comment counters in PostgreSQL? PostgreSQL 17: Part 4 or Commitfest 2024-01 How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need EDB unveils EDB Postgres AI provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial provided by Google News |
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