Elasticsearch vs OpenSearch: How They Differ?
The original Elasticsearch project was continued as an open-source project called OpenSearch by Amazon. Third parties were no longer able to continue providing Elasticsearch as a service because of the changes brought about by Elastic’s switch to a restrictive license. Based on the most recent open-source licensed releases of both Kibana and Elasticsearch, the community collaborated to develop and maintain OpenSearch.
AWS’s Open Distro for Elasticsearch, in its first form three years ago, resembled a mashup of many repositories that combined both Elasticsearch and Searchguard. At this early stage, the goal of integrating Elasticsearch with built-in security measures was still under development and far from being ready for production. AWS (Amazon Web Services), during its inception, did not offer Kibana multi-tenancy or role-based access controls. Fortunately, this is no longer the case, and the latest version of the AWS-backed OpenSearch Dashboards offers these functionalities as standard.
OpenSearch encourages all users to upgrade as soon as possible because the v1.0 release should be quite comparable to the Elasticsearch release on which it is based. This is done to make sure that your platforms can continue to get updates in the future.
In this article, we will address some of the most frequent doubts and queries users have about AWS Elasticsearch, and OpenSearch in this post because these three phrases are frequently used synonymously to refer to any Amazon-backed distribution of Elasticsearch and Kibana.
Based on the Lucene library, Amazon introduced Elasticsearch Service (Amazon ES) in 2015. This is a fully managed service which enables you to easily carry out interactive log analytics, real-time application monitoring, website search, and more.
ElasticSearch offers a distributed full-text search engine with a multitenant capability, an HTTP web interface, and documents that do not use any schema. Elasticsearch was created in Java and is licensed under two different licenses: the private (source-accessible) Elastic License for some parts and the Server-Side Public License, which is available as open source for Elasticsearch.
Amazon ElasticSearch has become a well-known solution for log analytics because it can take in copious amounts of log data. You may also get Amazon ES for a price that is a tenth of what regular hot storage costs by using the UltraWarm and cold storage tiers. As a result of Amazon ES’s integration with Amazon Kinesis Data Firehose, Logstash, Amazon CloudWatch Logs, and AWS IoT (Internet of Things), you can choose the safe data intake method that best suits your use case needs.
As well as many other languages, Amazon Elasticsearch’s official client applications are available in Java, .NET (C#), PHP, Python, and Apache Groovy. As per the DB-Engines ranking, Elasticsearch is the most popular enterprise search engine.
How does Amazon Elasticsearch work?
Using the API or ingestion tools like Logstash and Amazon Kinesis Firehose, you can submit data to Elasticsearch in the form of JSON documents. The original document is automatically stored by Elasticsearch along with a searchable reference in the cluster’s index. Using the Elasticsearch API, you can then search for and get the document. To view your data and create interactive dashboards, you may also combine Elasticsearch with the visualization tool Kibana.
After that, you may use the specific Elasticsearch API to look for the document and obtain it. In addition, you can use AWS Elasticsearch with any open-source visualizations tool to create insightful dashboards and visualize your data. Kibana, for example, is an Elasticsearch visualization tool. Below listed are some of the key features offered by Amazon Elasticsearch.
Some of AWS ElasticSearch’s Operational Features
- Simple setup, configuration, updates, event monitoring, alerting, SQL querying, and other administration processes
- It is extremely scalable, robust, and available.
- With Amazon Elasticsearch Service, security is the main priority.
- Because you only pay for what you really use, Amazon Elasticsearch Service is cost-effective.
- A warm storage tier called UltraWarm is included with Amazon Elasticsearch Service and provides storage for older and less frequently utilized data.
- The least expensive storage tier of S3’s cold storage allows you to keep all rarely accessed data on hand.
Moreover, Amazon Elasticsearch detects and replaces faulty Elasticsearch nodes automatically. Due to this, Elasticsearch software and self-managed infrastructure will have less of an impact on overhead costs. With customized AWS Identity and Access Management, you may continue to maintain control over access to your domain. Furthermore, you have the option to use manual or automatic snapshots to back up your data.
AWS ElasticSearch Benefits
- Value-adding in a short amount of time
Elasticsearch makes it simple to get started and develop applications for a range of use-cases with its simple REST-based APIs, straightforward HTTP interface, and use of schema-free JSON documents.
- Better performance
Elasticsearch’s distributed architecture enables it to handle enormous amounts of data concurrently, swiftly locating the best matches for your searches.
- Real-time operations
The typical execution time for Elasticsearch activities like reading or publishing data is under a second. As a result, you may utilize Elasticsearch for use cases involving near-real-time data, such as application monitoring and anomaly detection.
- Developing applications is simple
The Need for Open-Source Software
Open-source software is popular among developers for several reasons. The flexibility to utilize such programmed whenever and whenever one pleases is one of the most crucial factors. Elastic NV made a change to their approach to software licensing on January 21, 2021. The permissive 2.0 version of the Apache License will no longer be used to release new versions of Elasticsearch and Kibana after versions 7.10.2 and 7.10.2, respectively (ALv2). Elasticsearch and Kibana are instead being made available by Elastic NV under the Elastic license, with the source code also being made available under the Server-Side Public License or the Elastic License (SSPL). These licenses do not allow users the same freedom and are not open source.
Due to this, Amazon made the decision to develop and maintain OpenSearch, a branch of Elasticsearch and Kibana from the final ALv2 release that is community-driven and open-source. The OpenSearch project, of which version 1.0 was just launched, is one in which we are making a long-term investment.
With OpenSearch Dashboards, a highly scalable visualization tool, OpenSearch delivers quick access to massive volumes of data. The tool simplifies the process of analyzing data for users. Elasticsearch 7.10.2 and Kibana 7.10.2 were the original sources of OpenSearch and OpenSearch Dashboards. The Apache Lucene search library powers OpenSearch, Elasticsearch, and Apache Solr.
Launching Amazon OpenSearch service
Amazon updated the name of their Elasticsearch service to Amazon OpenSearch service to reflect the fact that it now supports OpenSearch 1.0. Despite the name change, the same experiences will still be offered without negatively affecting present operations, development methods, or commercial use. The Amazon OpenSearch Service offers 19 versions of ALv2 Elasticsearch 7.10 and earlier, as well as OpenSearch 1.0, for deployment and running.
Though ALv2 Elasticsearch versions will continue to get security and bug patches from Amazon, it will make use of OpenSearch and OpenSearch Dashboards to bring brand-new features and capabilities. You will not need to adjust your present client code or applications since Amazon OpenSearch Service APIs will be backward-compatible with the current service APIs. We will continue to support open source in OpenSearch clients.
Let us get down to know more about the features, services and benefits offered by AWS OpenSearch.
What is Amazon OpenSearch?
The OpenSearch project is a distributed, open-source search and analytics suite with a variety of applications, including online search, log analytics, and application monitoring in real-time. With the help of an integrated visualization tool called OpenSearch Dashboards, OpenSearch offers a highly scalable system for giving quick access and response to massive volumes of data. This tool makes it simple for users to examine their data. The Apache Lucene search library powers OpenSearch, Elasticsearch, and Apache Solr. Elasticsearch and Kibana were the original sources of OpenSearch and OpenSearch Dashboards.
Both OpenSearch and the original Elasticsearch OSS are supported by Amazon OpenSearch Service, the replacement for Amazon Elasticsearch Service. OpenSearch is a completely open-source search and analytics engine for applications such as log analytics, real-time application monitoring, and clickstream analysis. OpenSearch Service assists in the creation and launch of clusters while allowing you to use your preferred search engine.
Additionally, it automatically locates and replaces failing OpenSearch Service nodes, minimizing the overhead related to self-managed infrastructures. With just one API request or a few mouse clicks in the terminal, you can scale your cluster.
How does OpenSearch work?
As mentioned above, Amazon OpenSearch Service enables you to analyze logs interactively, monitor applications in real time, search websites, and more. OpenSearch is a free, distributed search and analytics platform based on Elasticsearch. The successor to Amazon Elasticsearch Service, Amazon OpenSearch Service, includes the most recent OpenSearch versions, support for 19 Elasticsearch versions and visualization tools provided by OpenSearch Dashboards and Kibana. With hundreds of thousands of clusters managed by Amazon OpenSearch Service and tens of thousands of active users, the service currently processes hundreds of trillions of queries every month.
Software installation, upgrades, patching, scalability, and cross-region replication are all handled by AWS without any downtime. The Amazon OpenSearch Service also includes a dashboard visualization tool called OpenSearch Dashboards that aids in the visualization of log and trace data as well as outcomes from machine learning-powered anomaly detection and search relevance ranking. Some of the qualitative features offered by OpenSearch are listed below.
- Managed OpenSearch
Utilize the power of open-source search and concentrate on analysis rather than managing your deployment and changing deployment configurations as requirements change.
For authentication, authorization, encryption, audit, and regulatory compliance, meet and maintain high security standards.
Deliver log and trace analytics solutions while creating interactive queries and quickly and nimbly viewing the data.
Embrace full-text search capabilities that are quick and scalable. Maintain control over rising analytics expenses for UltraWarm, and cold tiers. All features are offered with no upsell.
AWS OpenSearch Use Cases
- Monitoring and fixing infrastructure issues
Utilize observability logs, metrics, and traces to conveniently store and analyze data for thorough visibility into your system performance. Set up automatic warnings for when your system performs poorly and track out the source of any availability problems.
- Control event and security information (SIEM)
Centralize and analyze logs from diverse apps and systems throughout your network for real-time threat discovery and event management.
- Make customized, seamless search possible
With a speedy, tailored search experience within your applications, websites, and data lake catalogues, you can assist users in finding relevant data quickly.
Promote the quality of the application, efficiently detect, and fix issues, and provide better client experiences.
Elasticsearch vs OpenSearch
As mentioned earlier, the reason for AWS to introduce OpenSearch was to provide developers with open-source software which has the flexibility to be used whenever and wherever they want. As new versions of Elasticsearch and Kibana will not be released under the liberal ALv2 license, it does not allow users the same freedoms. Due to this, AWS decided to fork Elasticsearch and Kibana from the most recent ALv2 release and maintain it. The fork, known as OpenSearch, is accessible through ALv2.
To put it briefly, AWS Elasticsearch Service (Amazon ES) is a subscription-based service offered by Amazon since 2015. This service provides managed Elasticsearch services.
Amazon OpenSearch Service replaces Amazon Elasticsearch Service and offers OpenSearch as a managed service. It was announced on September 8th 2021.
It was announced on June 25 2021 that OpenSearch would be renamed Open Distro for Elasticsearch (ODFE) as the old ODFE site will be decommissioned sequentially in the near future.
As of September 8th, 2021, OpenSearch and OpenSearch dashboards have replaced Open Distro for Elasticsearch. The latest version of the Elastic Stack is fully open-source.
Elasticsearch and Kibana have been distributed through Amazon Web Services, excluding Logstash from the development process.
According to the official AWS open-source blog, the Amazon Elasticsearch Service was changed to the Amazon OpenSearch Service on September 8th, 2021.
Few operational features of OpenSearch you may not find in ElasticSearch
- Advance Security
provides capabilities for audits, encryption, authentication, and authorization. Integrations with Kerberos, Active Directory, SAML, LDAP, JSON web tokens, and other systems are among them. In addition, OpenSearch offers fine-grained, role-based access control for fields, documents, and indices.
- SQL Query Syntax
gives the well-known SQL query syntax. To analyze your data, utilize aggregations, and group by clauses. You can choose the best format by reading data as either CSV tables or JSON documents.
Reports from dashboards, saved searches, alarms, and visualizations can be scheduled, exported, and shared.
- Anomaly Detection
To automatically find abnormalities as your data is being ingested, use machine learning anomaly detection based on the Random Cut Forest (RCF) method. To monitor data instantly and automatically issue alarm alerts, combine with alerting.
- Index Management
Create unique policies, apply them to indices, index patterns, and transforms, and use them to automate common index administration operations like rollover and delete.
- Performance Analyzer and RCA framework
Query various metrics and aggregations of cluster performance. To quickly show and examine such metrics, use PerfTop, the command-line interface (CLI). Investigate performance and reliability issues in clusters using the root cause analysis (RCA) paradigm.
- Asynchronous Search
Asynchronous Search queries allow you to execute sophisticated queries without being concerned about the query timing out. Follow the development of your query and get your partial results as they come in.
While users benefit immensely from the OpenSearch features mentioned above, Elasticsearch offers exceptional product features and maturity. Being a cloud-neutral product that is tightly integrated into a variety of clouds, Amazon ES provides the technological know-how developed over a decade of working on these solutions.
With Amazon OpenSearch Service, AWS has taken over from Amazon Elasticsearch Service. With the name changed to Amazon OpenSearch Service, the service will no longer provide access to current or upcoming Elasticsearch releases. Instead, it will provide access to earlier open-source Elasticsearch (versions prior to 7.10.2) and OpenSearch releases.
While they may still be able to communicate with one another, OpenSearch and Elasticsearch are no longer the same. Both OpenSearch and the older (Apache License v2.0) open source Elasticsearch are compatible with the OpenSearch Service configuration API.
So, if you would prefer to use a platform that is prepared to go live in just a few minutes and has access to the best features of OpenSearch and OpenSearch Dashboards, consult our specialists at Webuters. We assist in saving engineers and technicians from the time-consuming setup that is frequently required as well as the following upkeep and optimization of Open-Source technologies.