DBMS > Amazon DynamoDB vs. Fauna vs. Microsoft Azure Data Explorer vs. OceanBase vs. PostgreSQL
System Properties Comparison Amazon DynamoDB vs. Fauna vs. Microsoft Azure Data Explorer vs. OceanBase vs. PostgreSQL
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Name | Amazon DynamoDB Xexclude from comparison | Fauna previously named FaunaDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | OceanBase Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure. | Fully managed big data interactive analytics platform | A distributed, high available RDBMS compatible with Oracle and MySQL | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Key-value store | Document store Graph DBMS Relational DBMS Time Series DBMS | Relational DBMS column oriented | 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 | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Wide column store | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/dynamodb | fauna.com | azure.microsoft.com/services/data-explorer | en.oceanbase.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/dynamodb | docs.fauna.com | docs.microsoft.com/en-us/azure/data-explorer | en.oceanbase.com/docs/oceanbase-database | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Fauna, Inc. | Microsoft | OceanBase previously Alibaba and Ant Group | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2014 | 2019 | 2010 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 4.3.0, April 2024 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free tier for a limited amount of database operations | commercial | commercial | Open Source Commercial license available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Scala | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | hosted | hosted | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | Fixed schema with schema-less datatypes (dynamic) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | 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 | yes | yes | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | no | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API | RESTful HTTP API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC ODP.NET Oracle Call Interface (OCI) Proprietary native API Table API | 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 | C# Go Java JavaScript Python Ruby Scala Swift | .Net Go Java JavaScript (Node.js) PowerShell Python R | Ada in MySQL-compatible model C in Oracle- and MySQL- compatible models C++ in Oracle- and MySQL- compatible models D in MySQL-compatible model Delphi in MySQL-compatible model Eiffel in MySQL-compatible model Erlang in MySQL-compatible model Haskell in MySQL-compatible model Java in Oracle- and MySQL- compatible models JavaScript (Node.js) in MySQL-compatible model Objective-C in MySQL-compatible model OCaml in MySQL-compatible model Perl in MySQL-compatible model PHP in MySQL-compatible model Python in MySQL-compatible model Ruby in MySQL-compatible model Scheme in MySQL-compatible model Tcl in MySQL-compatible model | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | user defined functions | Yes, possible languages: KQL, Python, R | PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode | 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 | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | horizontal partitioning consistent hashing | Sharding Implicit feature of the cloud service | horizontal partitioning (by hash, key, range, range columns, list, and list columns) | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Multi-source replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-source replication using Paxos | 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 | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | 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 | ACID | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | Identity management, authentication, and access control | Azure Active Directory Authentication | Access rights for users, groups and roles according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | Fauna previously named FaunaDB | Microsoft Azure Data Explorer | OceanBase | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | OceanBase Database is the world’s only native distributed database that has set new... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | High Availability : The five IDCs across three sites disaster recovery solution sets... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | OceanBase Database has helped over 400 customers across industries upgrade their... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | TPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Mulan PubL v2 license for open source community edition. Commercial license for enterprise... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | Fauna previously named FaunaDB | Microsoft Azure Data Explorer | OceanBase | 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 Monitoring PostgreSQL with Redgate Monitor Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Using Elasticsearch to Offload Search and Analytics from DynamoDB: Pros and Cons Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Migrating Uber's Ledger Data from DynamoDB to LedgerStore How Heroku reduced their operational overhead by migrating their 30 TB self-managed database from Amazon EC2 to ... provided by Google News Fauna Launches Distributed Document-Relational Database On Google Cloud Marketplace Slicing the Gordian Knot: A leap to real-time systems of truth Fauna Adds Transformative Schema-as-Code Capabilities to Enterprise Proven, Document-Relational Database Utah Natural Heritage Program Fauna Query Language tamed to appeal to developers provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services provided by Google News OceanBase Inks Agreement with NTU Singapore in Database Optimization and Green Computing Advancements Ant Group Will Cut Foreign Investors Out of Fast-Growing Database Business How Southeast Asia's Leading e-Wallets Saved Up to 40% in Database Costs - Fintech Singapore Haidilao’s 6-step recipe for successful digital transformation with OceanBase Alibaba's OceanBase distributed database aims at markets outside China provided by Google News Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... SolarWinds Unveils Enhanced Database Performance Analyzer with Advanced PostgreSQL Support ServiceNow trades MariaDB for RaptorDB (PostgreSQL) First Principles: Optimizing PostgreSQL for the cloud General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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