DBMS > Amazon Aurora vs. Amazon DynamoDB vs. PostgreSQL vs. SingleStore vs. Sphinx
System Properties Comparison Amazon Aurora vs. Amazon DynamoDB vs. PostgreSQL vs. SingleStore vs. Sphinx
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Name | Amazon Aurora Xexclude from comparison | Amazon DynamoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | MySQL and PostgreSQL compatible cloud service by Amazon | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Document store Key-value store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS Time Series DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/rds/aurora | aws.amazon.com/dynamodb | www.postgresql.org | www.singlestore.com | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | docs.aws.amazon.com/dynamodb | www.postgresql.org/docs | docs.singlestore.com | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Amazon | PostgreSQL Global Development Group www.postgresql.org/developer | SingleStore Inc. | Sphinx Technologies Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | 2013 | 2001 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 16.3, May 2024 | 8.5, January 2024 | 3.5.1, February 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial free tier for a limited amount of database operations | Open Source BSD | commercial free developer edition available | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C | C++, Go | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux 64 bit version required | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | 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. | yes | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | no | yes standard with numerous extensions | yes but no triggers and foreign keys | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC | RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Bash C C# Java JavaScript (Node.js) Python | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes by integration with AWS Lambda | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding hash partitioning | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | yes | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication stores two copies of each physical data partition on two separate nodes | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | no can define user-defined aggregate functions for map-reduce-style calculations | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID ACID across one or more tables within a single AWS account and region | ACID | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | 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 | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | Fine grained access control via users, groups and roles | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | Amazon DynamoDB | PostgreSQL | SingleStore former name was MemSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Customers in various industries worldwide including US and International Industry... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | F ree Tier and Enterprise Edition » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | Amazon DynamoDB | PostgreSQL | SingleStore former name was MemSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Amazon - the rising star in the DBMS market | 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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | The DB-Engines ranking includes now search engines Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ... Join the preview of Amazon Aurora Limitless Database | Amazon Web Services Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ... Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services provided by Google News Use Amazon DynamoDB incremental exports to drive continuous data retention | Amazon Web Services AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services provided by Google News PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files Announcing watsonx.ai and SingleStore for generative AI applications 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 Google's Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack How to Build 600+ Links in One Month provided by Google News |
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