DBMS > Amazon DynamoDB vs. Faircom DB vs. Kinetica vs. Netezza vs. PostgreSQL
System Properties Comparison Amazon DynamoDB vs. Faircom DB vs. Kinetica vs. Netezza vs. PostgreSQL
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| Name | Amazon DynamoDB Xexclude from comparison | Faircom DB  formerly c-treeACE Xexclude from comparison | Kinetica Xexclude from comparison | Netezza Also called PureData System for Analytics by IBM Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | Fully vectorized database across both GPUs and CPUs | Data warehouse and analytics appliance part of IBM PureSystems | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value store | Key-value store Relational DBMS | Relational DBMS | 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 | Spatial DBMS Time Series DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | www.faircom.com/products/faircom-db | www.kinetica.com | www.ibm.com/products/netezza | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | docs.kinetica.com | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | FairCom Corporation | Kinetica | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 1979 | 2012 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | V12, November 2020 | 7.1, August 2021 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free tier for a limited amount of database operations | commercial Restricted, free version available | commercial | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | ANSI C, C++ | C, C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | Linux | Linux included in appliance | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema free, schema optional, schema required, partial schema, | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes, ANSI SQL Types, JSON, typed binary structures | yes | 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 | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | yes, ANSI SQL with proprietary extensions | SQL-like DML and DDL statements | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | JDBC ODBC RESTful HTTP API | JDBC ODBC OLE DB | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | C++ Java JavaScript (Node.js) Python | C C++ Fortran Java Lua Perl Python R | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes .Net, JavaScript, C/C++ | user defined functions | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by integration with AWS Lambda | yes | yes triggers when inserted values for one or more columns fall within a specified range | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | Source-replica replication | Source-replica replication | 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) | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | tunable from ACID to Eventually Consistent | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | Yes, tunable from durable to delayed durability to in-memory | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes GPU vRAM or System RAM | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 with additional protections for files | Access rights for users and roles on table level | Users with fine-grained authorization concept | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Amazon DynamoDB | Faircom DB formerly c-treeACE | Kinetica | Netezza Also called PureData System for Analytics by IBM | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 Using the circuit-breaker pattern with AWS Lambda extensions and Amazon DynamoDB | 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 Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services provided by Google News FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple' FairCom kicks off new era of database technology USA - English provided by Google News Kinetica Delivers Real-Time Vector Similarity Search Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise Transforming spatiotemporal data analysis with GPUs and generative AI provided by Google News Roundup: Telehouse, Cloudera, Netezza, EMC IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS AWS and IBM Netezza come out in support of Iceberg in table format face-off How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime | Amazon Web Services IBM Brings Back a Netezza, Attacks Yellowbrick provided by Google News How to implement a better like, views, comment counters in PostgreSQL? Automatically Generate Types for Your PostgreSQL Database Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Enterprise DB begins rolling AI features into PostgreSQL provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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