The YugaByte Database Blog

Thoughts on open source, cloud native and distributed databases

Data Modeling Basics – PostgreSQL vs. Cassandra vs. MongoDB

Application developers usually spend considerable time evaluating multiple operational databases to find that one database that’s best fit for their workload needs. These needs include simplified data modeling, transactional guarantees, read/write performance, horizontal scaling and fault tolerance. Traditionally, this selection starts out with the SQL vs. NoSQL database categories because each category presents a clear set of trade-offs. High performance in terms of low latency and high throughput is usually treated as a non-compromisable requirement and hence is expected in any database chosen.

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Distributed Backups in Multi-Region YugaByte DB Clusters

Our post Getting Started with Distributed Backups in YugaByte DB details the core architecture powering distributed backups in YugaByte DB. It also highlights a few backup/restore operations in a single region, multi-AZ cluster. In this post, we perform distributed backups in a multi-region YugaByte DB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.

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Getting Started with Distributed Backups in YugaByte DB

YugaByte DB is a distributed database with a Google Spanner-inspired strongly consistent replication architecture that is purpose-built for high availability and high performance. This architecture allows administrators to place replicas in independent fault domains, which can be either availability zones or racks in a single region or different regions altogether. These types of multi-AZ or multi-region deployments have the immediate advantage of guaranteeing organizations a higher order of resilience in the event of a zone or region failure.

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Presto on YugaByte DB: Interactive OLAP SQL Queries Made Easy

Presto is a distributed SQL query engine optimized for OLAP queries at interactive speed. It was created by Facebook and open-sourced in 2012. Since then, it has gained widespread adoption and become a tool of choice for interactive analytics. It supports standard ANSI SQL, including complex queries, aggregations, joins, and window functions. It has a connector architecture to query data from many data sources such as SQL and NoSQL databases as well as traditional big data platforms such as Hive/Hadoop.

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Are MongoDB’s ACID Transactions Ready for High Performance Applications?

Web app developers initially adopted MongoDB for its ability to model data as “schemaless” JSON documents. This was a welcome relief to many who were previously bitten by the rigid structure and schema constraints of relational databases. However, two critical concerns that have been a thorn on MongoDB’s side over the years are that of data durability and ACID transactions.

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Introducing YSQL: A PostgreSQL Compatible Distributed SQL API for YugaByte DB

YugaByte’s mission from day one has been to simplify operational database infrastructure. We are doing so by bringing together the best aspects of SQL and NoSQL into a single transactional, high-performance database. I am pleased to announce a key milestone in our mission with the formal introduction of YSQL, YugaByte DB’s PostgreSQL-compatible distributed SQL API, as part of the recent 1.1 release.

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YugaByte DB 1.1 New Feature: Public IPs to Simplify Multi or Hybrid Cloud Database Deployments

Welcome to another post in our ongoing series that highlights new features from the latest 1.1 release announced last week. Today we are going to look at the importance of public IP addresses and hostnames in simplifying multi-cloud and hybrid cloud deployments.

In modern cloud deployments, servers often have a combination of private IP addresses (used in the private LAN and often the IP address of the network interface on the server),

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YugaByte DB 1.1 New Feature: Document Data Modeling with the JSON Data Type

Welcome to another post in our ongoing series that highlights new features from the latest 1.1 release announced last week. Today we are going to look at document data modeling using the native JSON data type available in YugaByte DB’s Cassandra compatible YCQL API. Note that this data type is specific to YugaByte DB and is not part of the standard Cassandra Query Language (CQL).

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YugaByte DB 1.1 New Feature: Speeding Up Queries with Secondary Indexes

Welcome to another post from our ongoing series where we highlight a new feature from the latest 1.1 release! Today we are going to look at secondary indexes.

Defining Secondary Indexes

A database index is a data structure that improves the speed of data retrieval operations on a database table. Typically, databases are very efficient at looking up data by the primary key.

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