DBMS > Amazon DynamoDB vs. IBM Db2 vs. PostgreSQL vs. Riak TS vs. SingleStore
System Properties Comparison Amazon DynamoDB vs. IBM Db2 vs. PostgreSQL vs. Riak TS vs. SingleStore
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| Name | Amazon DynamoDB Xexclude from comparison | IBM Db2  formerly named DB2 or IBM Database 2 Xexclude from comparison | PostgreSQL Xexclude from comparison | Riak TS Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Common in IBM host environments, 2 different versions for host and Windows/Linux | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value store | Relational DBMS Since Version 10.5 support for JSON/BSON documents compatible with MongoDB | 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 | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store RDF store in Db2 LUW (Linux, Unix, Windows)Spatial DBMS with Db2 Spatial Extender | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS Time Series DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | www.ibm.com/products/db2 | www.postgresql.org | www.singlestore.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | www.ibm.com/docs/en/db2 | www.postgresql.org/docs | www.tiot.jp/riak-docs/riak/ts/latest | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | Open Source, formerly Basho Technologies | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 1983 host version | 1989 1989: Postgres, 1996: PostgreSQL | 2015 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 12.1, October 2016 | 16.3, May 2024 | 3.0.0, September 2022 | 8.5, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free tier for a limited amount of database operations | commercial free version is available | Open Source BSD | Open Source | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| 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 and C++ | C | Erlang | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | AIX HP-UX Linux Solaris Windows z/OS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | no | 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. | yes specific XML-type available, but no XML query functionality. | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | restricted | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | yes | yes standard with numerous extensions | yes, limited | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API | ADO.NET JDBC JSON style queries MongoDB compatibleODBC XQuery | ADO.NET JDBC native C library ODBC streaming API for large objects | HTTP API Native Erlang Interface | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | C C# C++ Cobol Delphi Fortran Java Perl PHP Python Ruby Visual Basic | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C unofficial client library C# C++ unofficial client libraryClojure unofficial client libraryDart unofficial client libraryErlang Go unofficial client libraryGroovy unofficial client libraryHaskell unofficial client libraryJava JavaScript unofficial client libraryLisp unofficial client libraryPerl unofficial client libraryPHP Python Ruby Scala unofficial client librarySmalltalk unofficial client library | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Erlang | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by integration with AWS Lambda | yes | yes | yes pre-commit hooks and post-commit hooks | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding only with Windows/Unix/Linux Version | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes | yes with separate tools (MQ, InfoSphere) | Source-replica replication other methods possible by using 3rd party extensions | selectable replication factor | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | no | yes | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate Consistency | Eventual Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes | no links between datasets can be stored | 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 | ACID | ACID | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | 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 rights according to SQL-standard | no | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DynamoDB | IBM Db2 formerly named DB2 or IBM Database 2 | PostgreSQL | Riak TS | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 DynamoDB | IBM Db2 formerly named DB2 or IBM Database 2 | PostgreSQL | Riak TS | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Uber Migrates 1 Trillion Records from DynamoDB to LedgerStore to Save $6 Million Annually Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Migrating Uber's Ledger Data from DynamoDB to LedgerStore Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs provided by Google News Use AWS DMS to migrate data from IBM Db2 DPF to an AWS target | Amazon Web Services IBM Collaborates with AWS to Launch a New Cloud Database Offering, Enabling Customers to Optimize Data ... IBM's vintage Db2 database jumps on AWS's cloud bandwagon Precisely Supports Amazon RDS for Db2 Service with Real-Time Data Integration Capabilities Precisely says it's smoothing migration of Db2 analytics data to AWS cloud – Blocks and Files provided by Google News How to implement a better like, views, comment counters in PostgreSQL? 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 At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements PostgreSQL 17: Part 4 or Commitfest 2024-01 provided by Google News New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications Best open source databases for IoT applications provided by Google News SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore update adds new tools to fuel GenAI, analytics provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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