Document Databases

DynamoDB

DynamoDB is Amazon Web Services' fully managed, proprietary NoSQL key-value/document database, launched 2012 and derived from the 2007 Dynamo paper; it has no version number, only continuous feature releases. On-demand pricing (since a 50% cut on Nov 1, 2024) is $0.625 per million write request units and $0.125 per million read request units (us-east-1); provisioned capacity runs $0.00065/WCU-hour and $0.00013/RCU-hour, with reserved capacity cutting up to 77%. Each global secondary index multiplies write cost — a write with 3 GSIs consumes 4x WRUs. Free tier: 25 WCU/RCU + 25GB storage/region. Prime Day 2025 peaked DynamoDB at 151 million requests/second across Alexa, Amazon.com, and fulfillment centers; AWS cites "hundreds of thousands" of customers. Current version/status: N/A — continuously-released managed service (on-demand throughput pricing cut 50%, Nov 1 2024). License: proprietary (AWS managed service, no self-hosted option). Pricing: On-demand: $0.625/million write request units + $0.125/million read request units (us-east-1, post-Nov-2024 cut); provisioned: $0.00065/WCU-hr + $0.00013/RCU-hr with reserved capacity up to 77% cheaper; free tier 25 WCU/RCU + 25GB storage per region; each GSI adds a full extra WRU per write. Maintained by Amazon Web Services (AWS).

Also known as: aws-dynamodb

🧊Why learn DynamoDB?

Pick DynamoDB when you're already on AWS and need single-digit-millisecond reads at unpredictable, spiky scale without touching a capacity knob — on-demand mode scales to zero and back with no ops burden. Skip it for anything needing multi-table joins, ad-hoc queries, or multi-cloud portability — grab Postgres (or MongoDB Atlas if you want documents with real query flexibility) instead. AWS's own docs admit the tradeoff: GSIs silently multiply your write bill (1+N per index), and access patterns must be modeled upfront — bolt on a new query shape later and you're often rebuilding indexes, not writing SQL. Known weakness: AWS's own guidance requires modeling every access pattern before designing the table/index schema — unlike SQL there's no ad-hoc querying, so adding a new query shape after launch usually means adding (and paying for) a new GSI rather than writing a new query.

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Compare DynamoDB

DynamoDB vs Mongodb Atlas→DynamoDB vs Azure Cosmos Db→DynamoDB vs Postgresql→

Learning Resources

Amazon DynamoDB Pricing (official)

Quotas in Amazon DynamoDB — Developer Guide

New – Amazon DynamoDB lowers pricing for on-demand throughput and global tables

Amazon DynamoDB vs ScyllaDB comparison

Related Tools

Aws Lambda Amazon S3 Cassandra Redis Aws Cloudformation

Alternatives to DynamoDB

Mongodb Atlas Azure Cosmos Db Postgresql

Other Document Databases

Academic Databases

Academic databases are specialized digital repositories that store and provide access to scholarly literature, research papers, theses, dissertations, and other academic publications. They are designed to support research and education by offering structured, searchable collections of peer-reviewed content, often with advanced indexing and citation features. These databases are essential tools for researchers, students, and institutions to discover and retrieve credible academic information.

Always On Availability Groups

Always On Availability Groups is a high-availability and disaster recovery solution in Microsoft SQL Server that provides database-level failover for groups of databases. It allows multiple copies of a set of databases (availability replicas) to be maintained across different servers, ensuring data redundancy and automatic failover in case of primary server failure. This feature supports both synchronous and asynchronous data replication modes to balance performance and data protection needs.

Amazon Aurora is a fully managed, MySQL and PostgreSQL-compatible relational database service built for the cloud. It combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases, offering up to five times the throughput of standard MySQL and three times that of PostgreSQL. Aurora automatically handles tasks like hardware provisioning, database setup, patching, backups, and replication, while providing high durability and availability through distributed, fault-tolerant, self-healing storage.

Amazon Aurora is a fully managed relational database service compatible with MySQL and PostgreSQL, offered as part of Amazon Web Services (AWS). It provides high performance, scalability, and availability by using a distributed, fault-tolerant storage system that automatically replicates data across multiple Availability Zones. Aurora is designed to deliver up to five times the throughput of standard MySQL and three times that of PostgreSQL while maintaining compatibility with existing applications.

Amazon Aurora Provisioned

Amazon Aurora Provisioned is a fully managed relational database service from AWS that offers high performance, scalability, and availability with MySQL and PostgreSQL compatibility. It uses a distributed, fault-tolerant storage system that automatically scales up to 128 TB per database instance, providing fast read replicas and continuous backup to Amazon S3. This provisioned model requires users to pre-allocate and pay for database instance capacity, making it suitable for predictable workloads.

Amazon Aurora Serverless

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.