Another hidden little Rails gem I found out about this week. Swap out your database engine: $ rails db:system:change —to=<new_db_type> For situations where you wanted to change from SQLite to PostgreSQL to get ready for production, for example. #dev #tips #ruby #ruby_on_rails

And how about 3 tips/tricks for your Oracle Database REST APIs? https://www.thatjeffsmith.com/archive/2022/10/3-ords-rest-api-tips-tricks-for-oracle-developers/

The fact that DuckDB isn't a data warehouse...is the whole point of DuckDB! Once you pull your head out of the snow or the bricks or wherever you spend most of your data engineering time, you will discover that there are data pipeline problems *everywhere* that benefit from data modeling and SQL!

2011 tech blogs are delightful

❄️ on the cloud 🦆 on laptop

☮️ A peaceful solution: your DBA thinks you are using Oracle, while your developers believe they are using MongoDB. docs.oracle.com/en/database/...

User experience is how you should chose a database

A MongoDB API on top of SQL databases

Dgraph: A distributed graph database designed for high-performance and scalability, enabling complex queries over large graph datasets. #Dgraph #GraphDatabase

Vertica: A columnar storage database optimized for high-performance analytics, ideal for data warehousing and business intelligence applications. #Vertica #Analytics

Firebird: An open-source SQL relational database known for its lightweight footprint and advanced features like stored procedures and triggers, great for embedded systems. #Firebird #OpenSource

Pivotal GemFire: An in-memory data grid that offers distributed SQL capabilities, allowing for low-latency data access and real-time analytics for large-scale applications. #GemFire #DistributedSQL

Greenplum: A massively parallel processing (MPP) database built on PostgreSQL, designed for data warehousing and analytics, capable of handling large-scale data. #Greenplum #DataWarehouse

CrateDB: A distributed SQL database optimized for machine data and analytics, providing scalability and support for real-time queries across large datasets. #CrateDB #DistributedSQL

MemSQL (now SingleStore): A distributed, in-memory SQL database that supports both transactional and analytical workloads, optimized for speed and real-time analytics. #SingleStore #DistributedSQL

ClustrixDB (now MariaDB X5): A distributed database designed for high availability and performance, particularly for online transaction processing, supporting SQL and NoSQL workloads. #ClustrixDB #DistributedSQL

NuoDB: A distributed SQL database designed for cloud environments, focusing on scale-out architecture while maintaining ACID compliance for transactional workloads. #NuoDB #CloudDatabase

TiDB: An open-source distributed SQL database that provides horizontal scalability and strong consistency, designed for online transaction processing (OLTP) and online analytical processing (OLAP) workloads. #TiDB #DistributedSQL

Google Spanner: A fully managed, horizontally scalable database service that offers global transactions with strong consistency and SQL support, ideal for large-scale applications. #GoogleSpanner #CloudDatabase

YugabyteDB: An open-source, distributed SQL database that offers strong consistency, horizontal scalability, and high availability, designed for cloud-native applications. #YugabyteDB #DistributedSQL

Microsoft Access: A desktop relational database management system that integrates well with other Microsoft products, suitable for small to medium-sized applications. #MicrosoftAccess #DesktopDatabase

Couchbase: A distributed NoSQL database that offers key-value storage with strong consistency and built-in caching, suitable for web and mobile applications. #Couchbase #NoSQL

InfluxDB: A time-series database optimized for high-write loads and real-time analytics, ideal for monitoring systems and IoT applications. #InfluxDB #TimeSeriesData

ArangoDB: A multi-model database that combines document, graph, and key-value data models, providing flexibility for complex data relationships. #ArangoDB #MultiModel

TimescaleDB: A time-series database built on PostgreSQL, optimized for handling time-series data, ideal for IoT and monitoring applications. #TimescaleDB #TimeSeries

IBM Db2: Offers advanced AI-driven analytics and hybrid cloud capabilities, making it suitable for enterprise applications with large volumes of data. #Db2 #EnterpriseDB

Teradata: Known for its data warehousing capabilities, it excels in handling large-scale analytics and complex queries for business intelligence. #Teradata #DataWarehousing

HBase: A NoSQL database that runs on top of HDFS, designed for real-time read/write access to large datasets, often used in big data applications. #HBase #BigData

Firebase Realtime Database: A NoSQL cloud database that allows real-time data synchronization across clients, making it perfect for mobile and web applications needing instant updates. #Firebase #RealtimeDatabase

Amazon DynamoDB: A fully managed NoSQL database service that provides fast and predictable performance with seamless scalability, ideal for serverless applications. #DynamoDB #AWS

CockroachDB: A distributed SQL database designed for cloud-native applications, providing high resilience and horizontal scalability, perfect for global applications. #CockroachDB #CloudNative

MariaDB: A MySQL fork offering enhanced performance and additional features like Galera Cluster for synchronous multi-master replication, making it a robust choice for high-availability scenarios. #MariaDB #OpenSource

Neo4j: A graph database designed for relationship-heavy data, making it great for social networks, recommendation engines, and fraud detection. #Neo4j #GraphDatabases

Elasticsearch: A distributed search and analytics engine, specialized in full-text search and data exploration at scale. #Elasticsearch #Search

SQLite: A lightweight, serverless SQL database, ideal for mobile apps and local storage solutions. #SQLite #EmbeddedDatabases

Redis: An in-memory data store known for extreme speed, used in caching, session management, and real-time analytics. #Redis #InMemory

Cassandra: Designed for high availability and handling large volumes of data, it’s perfect for distributed, real-time applications. #Cassandra #BigData

MongoDB: A NoSQL database with document-oriented storage, making it scalable and flexible for unstructured data. #MongoDB #NoSQL

Microsoft SQL Server: Offers seamless integration with Microsoft products and excellent data warehousing features, ideal for enterprise applications. #SQLServer

MySQL: Reliable and fast, with simple deployment, making it popular for web applications and read-heavy workloads. #MySQL #WebDevelopment

PostgreSQL: An open-source powerhouse with extensibility, ACID compliance, and JSONB support—great for complex queries and data analytics. #PostgreSQL #OpenSource

Oracle Database: Known for advanced multi-version concurrency control and strong PL/SQL support, perfect for high-volume, mission-critical workloads. #OracleDatabase