OpenSearch and Elasticsearch are powerful search engines with a common history but important differences. This blog will compare their similarities and differences to help you choose the best option for your project.
Are you on the hunt for a powerful search engine for your project but can't decide between OpenSearch and Elasticsearch?
You're not alone! While both engines have much in common, they also have some important differences. And that can impact your project's performance and scalability.
In case you're unfamiliar, OpenSearch and Elasticsearch are open-source, distributed search engines. Elasticsearch has been in existence for more than a decade.
It is widely used in various enterprise applications due to its exceptional performance, scalability, and ease of use.
OpenSearch, on the other hand, is a recent fork of Elasticsearch that was created in response to concerns about the future of the project's open-source development.
If you're trying to decide which of these search engines is right for you, you've come to the right place!
This blog will compare OpenSearch and Elasticsearch and explore their similarities and differences to help you make an informed decision.
Whether you want to optimize performance, scale your application, or manage costs, we've got you covered. Let's dive in and see which search engine reigns supreme!
- What is Amazon OpenSearch & What is it Used for?
- What is Elasticsearch?
- What is Open Distro for Elasticsearch (ODFE)?
- OpenSearch vs. Elasticsearch: Know the Differences
- Elasticsearch vs. OpenSearch - Installation & Configuration
- Elasticsearch vs. OpenSearch - Features
- Elasticsearch vs. AWS OpenSearch - Query Types
- OpenSearch vs. Elasticsearch - Performance
- AWS OpenSearch vs. Elasticsearch Pricing - Cost Comparison
- OpenSearch vs. Elasticsearch - Graylog
- OpenSearch vs. Elasticsearch - License
- AWS OpenSearch vs. Elasticsearch - Use Cases
- What Features of Amazon OpenSearch Service are not Available in Elasticsearch?
- Advanced Security
- SQL Query Syntax
- Anomaly Detection
- Performance Analyzer and RCA Framework
- Asynchronous Search
- Should You Shift to Amazon OpenSearch?
What is Amazon OpenSearch & What is it Used for?
Developers can use OpenSearch, a fully managed, open-source search and analytics service, to analyze large datasets in real-time.
It is built on top of Elasticsearch and compatible with Elasticsearch APIs and drivers, making it easy to get started.
Amazon designed OpenSearch to be flexible and scalable, so it can meet the needs of small and large-scale enterprise applications.
The service is fully managed by Amazon, which means they manage the underlying infrastructure, allowing developers to focus on application development.
What is Elasticsearch?
Simply, Elasticsearch is a distributed search and analytics engine that's designed to handle large volumes of data quickly and efficiently.
It's open-source, easy to use, and highly scalable, making it a top choice for developers across industries.
Elasticsearch's power lies in its ability to handle complex search queries and provide real-time insights into large datasets.
It's built on the Apache Lucene search library and compatible with various APIs, including RESTful ones. That makes it easy for developers to integrate into their applications.
What sets Elasticsearch apart is its ability to scale horizontally. That means that it can handle large volumes of data with ease.
It's also designed to be fault-tolerant, meaning it can handle node failures and other issues gracefully without affecting search performance.
Also Read: How to Migrate from AWS to Azure?
What is Open Distro for Elasticsearch (ODFE)?
ODFE is a distribution of Elasticsearch that's designed to provide additional security, alerting, and SQL capabilities.
It's open-source and built on top of Elasticsearch. That makes it a top choice for developers who need additional features beyond what Elasticsearch provides out of the box.
ODFE's security features include role-based access control, encryption for data at rest and in transit, and audit logging. These features are crucial for organizations that must secure their data and comply with regulations like GDPR or HIPAA.
It also provides additional alerting capabilities that allow developers to set up custom alerts based on specific conditions. This feature is useful for monitoring system health or detecting anomalies in large datasets.
Another standout feature of ODFE is its SQL capabilities, which allow developers to query Elasticsearch using SQL syntax.
This makes it easier for developers more familiar with SQL to work with Elasticsearch. It helps in reducing the learning curve and speeding up development time.
Also Read: What is Containerization?
OpenSearch vs. Elasticsearch: Know the Differences
OpenSearch and Elasticsearch are two powerful search engines widely used in enterprise applications.
While they share many similarities, there are also key differences between them that developers should be aware of.
In this article, we will explore the differences between OpenSearch and Elasticsearch. So you can decide on which one to use in your next project.
Elasticsearch vs. OpenSearch - Installation & Configuration
Elasticsearch provides official packages for various operating systems, making installation relatively easy.
The first step is to download the appropriate package for your system from the Elasticsearch downloads page.
Once the package has been downloaded, it can be installed using the package manager or manually extracting the files.
Once Elasticsearch is installed, it can be configured by editing the elasticsearch.yml configuration file. This file is located in the config directory of the Elasticsearch installation.
On the other hand, OpenSearch requires building from a source or using community-provided packages.
The OpenSearch documentation provides detailed instructions for building from source, but community packages are also available for several operating systems.
These packages can be downloaded from the OpenSearch website or community repositories.
Once OpenSearch is installed, it can be configured by editing the opensearch.yml configuration file. This file is located in the config directory of the OpenSearch installation.
Like Elasticsearch, the opensearch.yml file contains a variety of settings that can be adjusted. That includes network settings, memory usage, and node configuration.
Elasticsearch vs. OpenSearch - Features
Elasticsearch offers a powerful search and analytics engine that supports real-time search and dynamic mapping. It also has robust querying capabilities, with support for full-text search, geospatial search, and more.
Elasticsearch also offers several built-in analyzers for handling text data and support for custom analyzers.
Along with search capabilities, Elasticsearch also includes features such as index management, document versioning, and data replication for high availability.
It also supports plugins and integrations with various other tools and platforms.
OpenSearch shares many of its features but with a focus on open-source values and community-driven development.
OpenSearch includes all of Elasticsearch's core search and analytics features and supports additional plugins and integrations the community provides.
It also focuses on security and compliance, with built-in support for security features such as encryption and access control.
OpenSearch also includes support for anomaly detection and alerting, which can be useful for monitoring and troubleshooting search issues.
Also Read: Differences between Grafana and Datadog
Elasticsearch vs. AWS OpenSearch - Query Types
Regarding standard query types, Elasticsearch and AWS OpenSearch support common queries like full-text, term, and match queries.
Elasticsearch also offers advanced query types such as:
These queries enable you to search for documents based on geographic location data, such as distance from a specific point or within a specific polygon.
"More like this" queries
These queries allow you to find similar documents to a given document based on its content.
These queries enable you to write custom scripts to define complex search logic.
These queries enable you to search for sequences of terms within a document.
Elasticsearch also offers specialized queries for specific use cases, such as the nested query for searching within nested objects or the fuzzy query for searching for similar terms with minor spelling variations.
AWS OpenSearch, on the other hand, provides support for queries such as:
These allow you to search for a specific string of text within a document or set of documents.
These enable you to search for specific terms or phrases within a document.
It is used to combine data from multiple indices or data sources.
It is useful for matching specific sequences of terms within a field
Geographic and XY queries
It enables you to search for data based on geographic coordinates or shapes. It includes finding all documents within a certain distance of a particular location.
OpenSearch vs. Elasticsearch - Performance
Elasticsearch and OpenSearch are known for their speed and efficiency in handling large amounts of data. However, there are some differences between the two in terms of performance.
Latency for search queries
Elasticsearch is generally faster than OpenSearch in terms of indexing speed. Given it uses a default configuration that allows for faster indexing.
On the other hand, OpenSearch has a more optimized query execution engine and is better at handling complex queries. It also has lower latency for search queries.
Elasticsearch and OpenSearch can be scaled horizontally to handle large amounts of data. But OpenSearch has additional scaling features, such as shard placement awareness and automatic shard rebalancing.
Both platforms also support caching and load balancing to help optimize performance.
Ultimately, the performance of Elasticsearch vs. OpenSearch will depend on your specific use and the resources available to your organization.
However, both platforms have a reputation for fast and reliable search performance.
AWS OpenSearch vs. Elasticsearch Pricing - Cost Comparison
Regarding pricing, Elasticsearch and AWS OpenSearch offer different options.
Elasticsearch offers a free trial period, and their Standard plan starts as low as $95 per month. They also have Gold, Platinum, and Enterprise plans that offer additional features and can cost up to $175 monthly.
These plans offer security, alerting, and machine learning capabilities.
On the other hand, AWS OpenSearch is free on the OpenSearch Service with AWS Free Tier. Customers in the AWS Free Tier get up to 750 hours per month of a t2.small.search or t3.small.search instance.
These are entry-level instances typically used for test workloads and 10 GB per month of optional Amazon Elastic Block Store (EBS) storage.
Users exceeding the Free Tier usage limits will be charged the OpenSearch Service rates for the additional resources. The service also offers paid plans with more advanced features and support options.
Ultimately, the choice between Elasticsearch and AWS OpenSearch may come down to your organization's specific needs and budget.
Also Read: AWS Cost Optimization Tools & Best Practices
OpenSearch vs. Elasticsearch - Graylog
OpenSearch and Elasticsearch are popular for implementing a centralized logging solution like Graylog.
Graylog is an open-source log management system that collects, indexes, and analyzes data from various sources.
Both OpenSearch and Elasticsearch offer integration with Graylog. Graylog can use its search and indexing capabilities to efficiently query and retrieve log data.
Graylog out of the box supports Elasticsearch and it's easy to configure to use OpenSearch.
OpenSearch is designed to be compatible with the latest version of Elasticsearch. This means that OpenSearch can serve as a drop-in replacement for Elasticsearch without significant changes to the Graylog configuration.
On the other hand, Elasticsearch's compatibility with OpenSearch is limited, and it may require some modifications to the Graylog configuration to work with OpenSearch.
OpenSearch vs. Elasticsearch - License
OpenSearch is licensed under the Apache License 2.0. It is an open-source license that allows users to use, modify, and distribute the software freely.
It is powered by the Apache Lucene and Powered by Apache Lucene and driven by the OpenSearch Project community.
On the other hand, Elasticsearch uses a dual licensing model.
While the source code is licensed under Apache 2.0, Elasticsearch and Kibana are dual-licensed under the Elastic License and Server Side Public License (SSPL). This gives users the choice of which license to apply.
AWS OpenSearch vs. Elasticsearch - Use Cases
Use Cases of AWS OpenSearch
Log analytics: AWS OpenSearch is ideal for processing large volumes of log data from various sources and creating dashboards and visualizations to analyze that data.
Enterprise search: OpenSearch can power search functionality for various applications, from eCommerce websites to knowledge management platforms.
Application search: Developers can use OpenSearch to build search functionality into web and mobile applications, providing users with fast, accurate results.
Data exploration: With OpenSearch, users can explore and analyze large data sets, uncovering insights and trends that might go unnoticed.
Security analytics: OpenSearch enables the detection and response to security threats in real-time by analyzing log data and identifying anomalies.
Use Cases of Elasticsearch
Analytics: Elasticsearch is a popular choice for data analytics, as it can quickly process large volumes of data and provide insights through dashboards and visualizations.
Fuzzy searching: Elasticsearch's search capabilities excel at fuzzy matching, making it ideal for use cases where users may misspell or mistype search terms.
Autocompletion and instant search: Elasticsearch provides fast, accurate search results, making it ideal for use cases where users need to see search suggestions and results as they type.
Multi-tenancy: Elasticsearch is highly scalable and can power search functionality for multiple applications or websites.
Machine learning: Elasticsearch integration with machine learning frameworks enables it to perform tasks such as anomaly detection, forecasting, and other predictive analytics.
What Features of Amazon OpenSearch Service are not Available in Elasticsearch?
Amazon OpenSearch Service offers several advanced features that are not available in Elasticsearch, including:
OpenSearch offers fine-grained, role-based access control to indices, documents, and fields, along with integrations with Active Directory, LDAP, SAML, Kerberos, and more.
SQL Query Syntax
OpenSearch provides the familiar SQL query syntax, allowing users to use aggregations, group by, and where clauses to investigate their data.
OpenSearch uses machine learning anomaly detection based on the Random Cut Forest (RCF) algorithm to automatically detect anomalies as data is ingested.
Performance Analyzer and RCA Framework
Users can query numerous cluster performance metrics and aggregations and use PerfTop. The command line interface (CLI) quickly displays and analyzes those metrics.
One can use the root cause analysis (RCA) framework to investigate performance and reliability issues in clusters.
OpenSearch lets users run complex queries without worrying about the query timing out, with queries running in the background.
Users can track query progress and retrieve partial results as they become available.
Should You Shift to Amazon OpenSearch?
Changing to Amazon OpenSearch or sticking with Elasticsearch depends on your specific needs and priorities.
OpenSearch may be the better choice if you value advanced security features, SQL query syntax, reporting, anomaly detection, index management, and trace analytics.
However, if you prioritize features like fuzzy searching, autocomplete, and instant search, Elasticsearch may still be the way to go.
Ultimately, it's important to carefully evaluate your requirements and weigh each option's pros and cons before deciding.
Also Read: Kubernetes vs OpenShift
Is OpenSearch the same as Elasticsearch?
No, OpenSearch is a community-driven, open-source search and analytics suite derived from Elasticsearch and Kibana. It offers similar functionality to Elasticsearch but has additional features and a different licensing model.
What is OpenSearch good for?
OpenSearch is good for ingesting, securing, searching, aggregating, viewing, and analyzing data for various use cases, including log analytics, application search, and enterprise search. It also offers advanced security features, SQL query syntax, reporting, anomaly detection, index management, and more.
What is the new name of Elasticsearch in AWS?
The new name of Elasticsearch in AWS is Amazon OpenSearch.
Is Elasticsearch SQL or NoSQL?
Elasticsearch is typically classified as a NoSQL database. This is because of its flexible data model and non-relational data storage and retrieval approach.
Is Elasticsearch a REST API?
Yes, Elasticsearch exposes a RESTful API that allows users to perform CRUD (Create, Read, Update, Delete) operations on the data stored in Elasticsearch. Users can interact with Elasticsearch using HTTP methods such as GET, PUT, POST, and DELETE through the API.