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Confluent VS Apache Lucene

Compare Confluent VS Apache Lucene and see what are their differences

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Confluent logo Confluent

Confluent offers a real-time data platform built around Apache Kafka.

Apache Lucene logo Apache Lucene

High-performance, full-featured text search engine library written entirely in Java.
  • Confluent Landing page
    Landing page //
    2023-10-22
  • Apache Lucene Landing page
    Landing page //
    2023-08-20

Confluent features and specs

  • Scalability
    Confluent is built on Apache Kafka, which allows for smooth scalability to handle growing data needs without significant performance degradation.
  • Real-Time Data Processing
    Confluent enables real-time streaming data processing, which is beneficial for applications requiring immediate data insights and actions.
  • Comprehensive Ecosystem
    Confluent provides a rich set of tools and connectors that integrate seamlessly with various data sources and sinks, making it easier to build and manage data pipelines.
  • Ease of Use
    Confluent offers an intuitive user interface and comprehensive documentation, which simplifies the setup and management of Kafka clusters.
  • Managed Service Option
    Confluent Cloud provides a fully managed Kafka service, reducing the operational burden on the engineering team and allowing businesses to focus on developing applications.
  • Advanced Security Features
    Confluent offers robust security features including encryption, SSL, ACLs, and more, ensuring that data streams are protected.
  • Strong Customer Support
    Confluent offers professional support and consultancy services which can be very helpful for enterprises requiring 24/7 support and expertise.

Possible disadvantages of Confluent

  • Cost
    Confluent can be expensive, especially for small to medium-sized businesses. The costs can grow significantly with scale and additional enterprise features.
  • Complexity
    Despite its ease of use, the underlying system’s complexity can pose a challenge, particularly for teams who are new to Kafka or streaming data technologies.
  • Resource Intensive
    Running Confluent on-premises can be resource-intensive, requiring significant computational and storage resources to maintain optimal performance.
  • Learning Curve
    For those unfamiliar with Kafka and streaming technologies, there is a steep learning curve which can lead to longer implementation times.
  • Vendor Lock-In
    Utilizing Confluent’s proprietary tools and connectors can result in vendor lock-in, making it difficult to switch to alternative solutions without considerable effort and reconfiguration.
  • Dependency on Cloud Provider
    If using Confluent Cloud, dependency on the cloud provider’s infrastructure may introduce compliance and control limitations, particularly for businesses with strict data sovereignty requirements.

Apache Lucene features and specs

  • High Performance
    Lucene is known for its high-performance indexing and searching capabilities, which makes it suitable for handling large volumes of data efficiently.
  • Scalability
    Lucene can scale effectively to handle large datasets and accommodate growing data needs without significant performance degradation.
  • Flexible Querying
    It offers a rich query language and supports complex queries, allowing developers to perform precise and advanced searches.
  • Open Source
    Being open-source, Lucene is free to use and has a supportive community, which enhances its features through contributions and plugins.
  • Extensive Ecosystem
    Lucene is part of a larger ecosystem with tools like Apache Solr and Elasticsearch, which provide additional functionalities and easier management.

Possible disadvantages of Apache Lucene

  • Complexity
    Lucene can be complex to set up and configure, requiring a good understanding of indexing and search concepts.
  • Limited Out-of-the-box Features
    Lucene is a low-level library and lacks some of the out-of-the-box features found in higher-level search platforms, necessitating more custom development.
  • Steeper Learning Curve
    Developers need to invest time to understand its API and functionalities fully, which can be challenging for beginners.
  • Java Dependency
    As a Java-based library, Lucene requires a Java environment, which might not suit all development stacks or teams preferring other languages.
  • No Built-in Distributed Features
    Lucene itself does not handle distributed search and indexing natively, requiring integration with other tools like Solr or Elasticsearch for distributed capabilities.

Confluent videos

1. Intro | Monitoring Kafka in Confluent Control Center

More videos:

  • Review - Jason Gustafson, Confluent: Revisiting Exactly One Semantics (EOS) | Bay Area Apache Kafka® Meetup
  • Review - CLEARER SKIN AFTER 1 USE‼️| Ancient Cosmetics Update✨| CONFLUENT & RETICULATED PAPILLOMATOSIS CURE?😩

Apache Lucene videos

Paper Review - "Apache Lucene 4." SIGIR 2012 workshop on open source information retrieval

More videos:

  • Review - Fundamentals of Information Retrieval, Illustration with Apache Lucene

Category Popularity

0-100% (relative to Confluent and Apache Lucene)
Stream Processing
100 100%
0% 0
Custom Search Engine
0 0%
100% 100
Big Data
100 100%
0% 0
Custom Search
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Confluent and Apache Lucene

Confluent Reviews

We have no reviews of Confluent yet.
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Apache Lucene Reviews

5 Open-Source Search Engines For your Website
Apache Lucene is a free and open-source search engine software library, originally written completely in Java. It is supported by the Apache Software Foundation and is released under the Apache Software License. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform.
Source: vishnuch.tech

Social recommendations and mentions

Based on our record, Apache Lucene should be more popular than Confluent. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Confluent mentions (1)

  • Spring Boot Event Streaming with Kafka
    We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 3 years ago

Apache Lucene mentions (7)

  • Looking for small libraries implemented in multiple langauges
    I have to find a few examples of relatively small programming libraries that has been rewritten/ported to C++, C# and Java. Example: Lucene (it isn't that small, but still shows what I'm looking for). Source: over 2 years ago
  • HBO Max needs to stop purging its content.
    He is talking about impacting the search algorithm. Putting a “+” sounds like it is negatively impacting search quality. Source: over 2 years ago
  • Whoever worked on Steam's search engine needs a raise.
    For example Lucene is a core project common to many search engines, lots of things built ontop of it. And there are similar libraries Https://lucene.apache.org/core/. Source: over 2 years ago
  • Prometheus vs Elasticsearch stack - Key concepts, features, and differences
    Full-text search Elasticsearch is built on top of Apache Lucene, an open-source information retrieval software. Apache Lucene enables Elasticsearch can perform complex full-text searches using a single or combination of word phrases against its No SQL database. - Source: dev.to / almost 3 years ago
  • A simple but efficient algorithm for searching a large dataset of objects?
    If I had control of the back end I would implement a full-text engine such as Lucene. Generate the lookup table as a batch job and then perform the FTS when the request comes in. If you try to do this real-time, your search will take exponentially longer the larger the data set gets. Source: about 3 years ago
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What are some alternatives?

When comparing Confluent and Apache Lucene, you can also consider the following products

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

OpenSearch - OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, and a visualization and user interface, OpenSearch Dashboards.