13 open-source projects similar to markets/jekyll-timeago, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Jekyll Timeago alternative.
Chrono is a JavaScript natural language date parser that converts unstructured text and relative date expressions into structured date objects. It functions as a multi-locale date parser and expression engine designed to resolve time expressions globally. The library is customizable, allowing for the definition of custom regular expression patterns and refinement rules to extract business-specific date formats. It provides mechanisms to resolve relative terms like tomorrow or next Friday based on a specific reference date. The system covers international date formatting across various region
Groupdate is a PostgreSQL time series aggregator and date grouping tool. It provides a set of SQL functions to group and aggregate temporal records into discrete buckets, such as days, weeks, or months, to calculate sums and averages for reports. The project focuses on ensuring continuous timelines through time series gap filling, which inserts default values for periods where no data exists. It also includes a temporal data formatter that converts grouped date-time keys into localized strings or custom formatting patterns. The tool covers broad temporal data operations, including time range
A collection of Ruby methods to deal with statutory and other holidays. You deserve a holiday!
Chronic is a pure Ruby natural language date parser.
Accurate current and historical timezones for Ruby with support for Geonames and Google latitude - longitude lookups.
Recurring events library for Ruby. Enumerable recurrence objects and convenient chainable interface.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
This project is a curated collection of programming exercises designed to build proficiency in numerical computing and data manipulation. It provides a structured learning path for mastering multidimensional array operations, vectorized arithmetic, and statistical analysis. The repository focuses on developing practical expertise in array-based workflows, emphasizing techniques such as memory management, efficient data processing, and the replacement of explicit loops with vectorized operations. Users engage with hands-on challenges that cover the full lifecycle of numerical data, from initia