![]() ![]() It allows one-to-many relationships between data.ĥ. They're a good fit when dealing with complex data models with many relationships, as they can directly represent these as object structures.Ĥ. Examples include MongoDB (document database), Cassandra (wide-column store), Redis (key-value), and Neo4j (graph database).ģ. They are schema-less and include four main types: document databases, key-value stores, wide-column stores, and graph databases. Examples include MySQL, PostgreSQL, Oracle, and SQL Server.Ģ. It organizes data into tables (relations) and relies on a schema that defines the structure of the data, including tables, fields, and the relationships between them. □ Instagram: #Databases #DataScience #BigData #TechTalk #SQL #NoSQL #DataEngineering #softwareengineering Stay on top of your career game by following me, Brij kishore Pandey, and activating notifications on my profile by clicking the (□ ) button. Maybe a project that stood out or a learning curve that surprised you?ĭon't keep them to yourself – let's get talking in the comments below! Have any interesting anecdotes or experiences about these databases? Remember, they're more than just digital storage units-they're integral to shaping our online experiences, from your favorite apps to the most complex cloud solutions. Step into the future armed with knowledge about these database types! ObjectDB and ZODB provide encapsulation, inheritance, polymorphism, and more. MongoDB and Couchbase excel in this space, offering efficient querying and flexibility. InfluxDB and Prometheus are top picks for their superior query performance.ĩ️⃣ □□□□□□□□ □□□□□□□□□ □: Store data in a flexible, document-like format (similar to JSON). Apache Cassandra and DataStax are well-known examples.Ĩ️⃣ □□□□-□□□□□□ □□□□□□□□□ ⏳: A dream for tracking changes over time, like stock prices or weather data. Ideal for analytical queries and efficient data compression. Think LinkedIn network analysis with Neo4j or AWS Neptune.ħ️⃣ □□□□□□□□ □□□□□□□□□ □: These databases store data by columns, not rows. MySQL, Oracle, and Microsoft SQL Server are stalwarts in this space.Ħ️⃣ □□□□□ □□□□□□□□□ □️: The social network of databases! They're champions in delivering deep insights about connections. Key players include CockroachDB, VoltDB, and NuoDB.ĥ️⃣ □□□ (□□□□□) □️: The classical choice! SQL databases store structured data in tables and support powerful queries. They're the backbone of blockchain technologies, with Apache HBase being a notable example.Ĥ️⃣ □□□□□□ □: It's the perfect blend of NoSQL scalability with SQL's reliability. ![]() They're the powerhouse behind Google Maps and Uber!ģ️⃣ □□□□□□ □□□□□□□□□ □: These databases stand for transparency and immutability. Storing and retrieving data becomes a cakewalk! Examples: Amazon QLDB, Redis, AWS DynamoDB.Ģ️⃣ □□□□□□□ □□□□□□□□□ □: Geography and technology entwine! These databases store geographic data (like coordinates for landmarks or cities). This year, let's turbocharge our tech acumen by exploring these 10 types of databases that are shaping the digital landscape !ġ️⃣ □□□-□□□□□ □□□□□□□□□ □️: Picture a colossal locker room. 10 Types of Databases You Must Know in 2023 ![]()
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