Found Elasticsearch vs Groonga

Overview

Found Elasticsearch

Stacks11

Followers15

Votes0

Groonga

Stacks2

Followers15

Votes0

GitHub Stars831

Forks120

Found Elasticsearch vs Groonga: What are the differences?

Data Structure and Query Language: Found Elasticsearch utilizes a document-based data structure and Query DSL (Domain Specific Language) for querying and searching data. On the other hand, Groonga employs a versatile and powerful data structure that includes tables, columns, and indexes, along with a SQL-like query language for data manipulation.
Use Cases and Scalability: Found Elasticsearch is widely used for log and event data analysis, as well as enterprise search and analytics due to its distributed nature and scalability. Groonga, on the other hand, is commonly utilized for full-text search, data aggregation, and real-time search applications, with a focus on performance and speed.
Indexing and Search Speed: Found Elasticsearch excels in indexing and search speed, providing near real-time search capabilities for large volumes of data. Groonga is known for its fast and efficient indexing process and search speed, making it suitable for applications that require quick access to data.
Ecosystem and Plugins: Elasticsearch has a rich ecosystem with a vast array of plugins and integrations available for various functionalities such as monitoring, visualization, and machine learning. Groonga, on the other hand, has a smaller but growing ecosystem with plugins for different data processing tasks and extensions for extending its functionality.
Deployment and Configuration: Found Elasticsearch offers easy deployment options using cloud services and provides a user-friendly interface for managing and configuring clusters. Groonga can be deployed on different operating systems and supports various configuration options for fine-tuning performance and resource utilization.
Community Support and Documentation: The Elasticsearch community is extensive and active, with a wealth of resources, forums, and documentation available for users. Groonga also has a dedicated community, although smaller in comparison, providing support and documentation for users seeking assistance or guidance.

In Summary, Elasticsearch and Groonga offer diverse capabilities in terms of data structure, query language, use cases, performance, deployment, and community support.

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CLI (Node.js)

Manual

Detailed Comparison

Found Elasticsearch	Groonga
Create your own fully managed and hosted Elasticsearch cluster. You get a dedicated cluster with reserved memory, giving you predictable performance. There are no arbitrary limits on how many indexes or documents you can store. Scale your clusters as and when needed, without any downtime.	It is an embeddable super fast full text search engine. It can be embedded into MySQL. Mroonga is a storage engine that is based on it.
Hosted and managed: You get your own fully hosted and managed Elasticsearch cluster. No need to host and maintain your own costly search infrastructure.; Reserved Memory and storage: Your clusters get reserved memory and storage. No shared clusters and no arbitrary limits on how many indexes or documents you can store.; Scalable and flexible: Start small, grow big. You can scale your cluster as and when needed, without any downtime. There are several Elasticsearch versions to choose from, and upgrading is easier than ever.; Developer friendly: Our HTTPS API is developer-friendly and existing Elasticsearch libraries such as Tire, PyES and others works out of the box. We even provide an unmodified Elasticsearch API, so for those who have an existing Elasticsearch integration it is easy to start using Found.; Security: Communication to and from our service is securely transmitted over HTTPS (SSL) and your data is stored behind multiple firewalls and proxies. All clusters run in isolated containers (LXC) and customizable ACLs allow for restricting access to trusted people and hosts.; Availability: For production and mission critical environments we provide replication and automatic failover, protecting your cluster against unplanned downtime. In addition, data is continuously backed up to Amazon S3. In the event of a datacenter failure, your cluster is automatically failed over to a working datacenter or, in the case of a catastrophic event, rebuilt from backup.; Multi region: Found Elasticsearch is available in multiple regions.; Found Elasticsearch is also available on Heroku, AppHarbor and CloudControl.	Storage Engine; Fast; Easy to use
Statistics
GitHub Stars -	GitHub Stars 831
GitHub Forks -	GitHub Forks 120
Stacks 11	Stacks 2
Followers 15	Followers 15
Votes 0	Votes 0
Integrations
No integrations available	Snowplow Kibana Couchbase Cloud 66 Datadog Redash Logstash

What are some alternatives to Found Elasticsearch, Groonga?

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

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.

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

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.

Swiftype

Swiftype is the easiest way to add great search to your website or mobile application.

Related Comparisons

Found Elasticsearch vs Groonga: What are the differences?

Data Structure and Query Language: Found Elasticsearch utilizes a document-based data structure and Query DSL (Domain Specific Language) for querying and searching data. On the other hand, Groonga employs a versatile and powerful data structure that includes tables, columns, and indexes, along with a SQL-like query language for data manipulation.
Use Cases and Scalability: Found Elasticsearch is widely used for log and event data analysis, as well as enterprise search and analytics due to its distributed nature and scalability. Groonga, on the other hand, is commonly utilized for full-text search, data aggregation, and real-time search applications, with a focus on performance and speed.
Indexing and Search Speed: Found Elasticsearch excels in indexing and search speed, providing near real-time search capabilities for large volumes of data. Groonga is known for its fast and efficient indexing process and search speed, making it suitable for applications that require quick access to data.
Ecosystem and Plugins: Elasticsearch has a rich ecosystem with a vast array of plugins and integrations available for various functionalities such as monitoring, visualization, and machine learning. Groonga, on the other hand, has a smaller but growing ecosystem with plugins for different data processing tasks and extensions for extending its functionality.
Deployment and Configuration: Found Elasticsearch offers easy deployment options using cloud services and provides a user-friendly interface for managing and configuring clusters. Groonga can be deployed on different operating systems and supports various configuration options for fine-tuning performance and resource utilization.
Community Support and Documentation: The Elasticsearch community is extensive and active, with a wealth of resources, forums, and documentation available for users. Groonga also has a dedicated community, although smaller in comparison, providing support and documentation for users seeking assistance or guidance.

In Summary, Elasticsearch and Groonga offer diverse capabilities in terms of data structure, query language, use cases, performance, deployment, and community support.

Found Elasticsearch vs Groonga

Overview