CQEngine vs Lucene

Overview

Lucene

Stacks175

Followers230

Votes2

CQEngine

Stacks3

Followers22

Votes0

GitHub Stars1.8K

Forks255

CQEngine vs Lucene: What are the differences?

Indexing Mechanism: CQEngine is an in-memory Java collection indexing engine that allows for fast querying of objects within the collection, while Lucene is a full-text search library for Java that allows for indexing and searching of textual data based on keywords.
Query Language: CQEngine provides a SQL-like query language to create complex queries based on attributes of objects in the collection, whereas Lucene uses a Query Parser to create queries based on full-text search terms, boosting relevance through scoring algorithms.
Search Flexibility: CQEngine is more suitable for indexing and querying Java objects with complex data structures and relationships within the collection, while Lucene excels in indexing and searching textual documents with support for features like fuzzy search, wildcard search, and proximity search.
Memory Usage: CQEngine being an in-memory indexing engine consumes more memory as it indexes the entire collection in memory, while Lucene allows for disk-based indexing which saves memory but can impact performance due to disk I/O operations.
Update Mechanism: CQEngine provides efficient mechanisms to update the index in real-time as objects are added, removed, or modified within the collection without significant performance overhead, whereas Lucene requires occasional index optimization and reindexing for better search performance after updates.
Scalability: CQEngine is more suitable for small to medium-sized collections due to its in-memory nature, while Lucene is more scalable for large-scale applications with support for distributed search capabilities in a clustered environment.

In Summary, CQEngine is optimized for in-memory indexing of Java objects with complex data structures and relationships using a SQL-like query language, while Lucene is tailored for full-text search of textual data with flexible search capabilities and support for disk-based indexing.

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Manual

Detailed Comparison

Lucene	CQEngine
Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.	It is a NoSQL indexing and Query Engine, for retrieving objects matching SQL-like queries from Java collections, with ultra-low latency
over 150GB/hour on modern hardware;small RAM requirements -- only 1MB heap;incremental indexing as fast as batch indexing;index size roughly 20-30% the size of text indexed;ranked searching -- best results returned first;many powerful query types: phrase queries, wildcard queries, proximity queries, range queries;fielded searching (e.g. title, author, contents);sorting by any field;multiple-index searching with merged results;allows simultaneous update and searching;flexible faceting, highlighting, joins and result grouping;fast, memory-efficient and typo-tolerant suggesters;pluggable ranking models, including the Vector Space Model and Okapi BM25;configurable storage engine (codecs)	Ultra-fast; Query engine; No SQL
Statistics
GitHub Stars -	GitHub Stars 1.8K
GitHub Forks -	GitHub Forks 255
Stacks 175	Stacks 3
Followers 230	Followers 22
Votes 2	Votes 0
Pros & Cons
Pros 1 Fast 1 Small	No community feedback yet
Integrations
Solr Java	MongoDB PostgreSQL Fastify MySQL

What are some alternatives to Lucene, CQEngine?

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Sphinx

It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

MkDocs

It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Related Comparisons

CQEngine vs Lucene: What are the differences?

Indexing Mechanism: CQEngine is an in-memory Java collection indexing engine that allows for fast querying of objects within the collection, while Lucene is a full-text search library for Java that allows for indexing and searching of textual data based on keywords.
Query Language: CQEngine provides a SQL-like query language to create complex queries based on attributes of objects in the collection, whereas Lucene uses a Query Parser to create queries based on full-text search terms, boosting relevance through scoring algorithms.
Search Flexibility: CQEngine is more suitable for indexing and querying Java objects with complex data structures and relationships within the collection, while Lucene excels in indexing and searching textual documents with support for features like fuzzy search, wildcard search, and proximity search.
Memory Usage: CQEngine being an in-memory indexing engine consumes more memory as it indexes the entire collection in memory, while Lucene allows for disk-based indexing which saves memory but can impact performance due to disk I/O operations.
Update Mechanism: CQEngine provides efficient mechanisms to update the index in real-time as objects are added, removed, or modified within the collection without significant performance overhead, whereas Lucene requires occasional index optimization and reindexing for better search performance after updates.
Scalability: CQEngine is more suitable for small to medium-sized collections due to its in-memory nature, while Lucene is more scalable for large-scale applications with support for distributed search capabilities in a clustered environment.

CQEngine vs Lucene

Overview