The OpenSearch open platform provides powerful real-time data search and analysis capabilities. With its scalability and efficiency, OpenSearch can process huge volumes of data and provide fast access to search results.
OpenSearch has powerful full-text search and ranking capabilities that allow you to efficiently and accurately find and sort results. This is especially useful for systems that need to accurately and quickly search large amounts of text data.
OpenSearch is a powerful data analytics tool that helps you make informed business decisions. Managed Service for OpenSearch has a variety of data analytics functionality: aggregation, filtering, sorting and grouping.
Managed Service for OpenSearch also provides logging and monitoring data, allowing you to track and analyze the performance of your OpenSearch cluster, identify problems and optimize performance.
The service provides a ready-made ClickHouse environment, freeing you from the need to deal with infrastructure setup and management. This allows you to focus on data utilization and analytics to get valuable results faster.
results.
The service provides data protection with encryption, access control and monitoring. Data backup and recovery mechanisms ensure reliability and safety of information of different types of importance.
Managed Service for ClickHouse provides flexible scaling of resources to meet the requirements of your application. You can easily add or remove nodes, allocate resources and manage load to get optimal system performance and availability.
Managed Service for ClickHouse seamlessly integrates with other services in the cloud platform, allowing you to create complete solutions and leverage the power of other services to process and analyze data.
The DBaaS concept involves storing and managing data in a cloud environment, where the user does not need to install and maintain a database - he gets a ready-made and optimized solution in the cloud.
Open source distributed streaming processing platform. Provides high throughput and ensures streamlined data delivery between producers and consumers. Ideal for streaming data processing, event-notification architecture implementation and real-time big data processing.
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High-performance open source columnar database. Provides fast analytics and big data processing. It is optimized to run complex analytical queries on large datasets. ClickHouse offers high speed, efficient resource utilization and scalability, making it a popular choice for real-time analytics and big data workloads.
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A distributed search and analytics system. It is well suited for scenarios where fast and scalable data access is required, such as site search, log analysis and real-time data monitoring.
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High-performance distributed database with great flexibility, scalability and parallel query processing. It is the best choice for analytical tasks and big data processing.
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A flexible NoSQL database optimized for storing unstructured data such as documents, images and social media. With easy scalability and high performance, MongoDB is the ideal choice for Big Data projects and applications requiring real-time data processing.
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A powerful relational database that provides high performance and reliability. It is optimally suited for web applications, e-commerce and CMS where handling large amounts of structured data is important.
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A powerful and reliable open source relational database. It has a wide range of features, supports ACID transactions and provides flexibility for storing and processing structured data. Supports extensions and provides powerful features for database developers and administrators.
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A fast, scalable storage system best suited for caching, sessions, message queues, and lightweight data analytics. Its flexibility in data structures and high performance make Redis a popular solution for web applications.
DiscoverProvide continuous protection and instant access to rapidly growing datasets. Highly scalable and cost effective storage that integrates with your application scenarios.
Distribute traffic and workloads in the most efficient way: no server downtime, overload or underutilization.
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OpenSearch is a scalable system of open source search and analytics tools that allow you to work with large amounts of data. OpenSearch is developed by A9.com, a subsidiary of Amazon.com, based on the Elasticsearch source code. OpenSearch development was initiated when Elastic NV, the developer of Elasticsearch, announced its intention to abandon its open source policy in new versions of its product.
OpenSearch has a storage and search engine, a web interface, an integrated visualization tool, OpenSearch Dashboards, making it easy for users to explore data. OpenSearch also includes a number of plugins to extend the functionality and utilize the capabilities of the Elasticsearch engine.
OpenSearch can be used as a tool to retrieve, protect, search, aggregate, view, and analyze data, for a variety of tasks, such as log analysis, application search, and enterprise search. OpenSearch enables the following functionality:
Here are just a few examples of how OpenSearch is being used for large-scale projects:
Managed Service for OpenSearch is a service that provides a ready-to-use OpenSearch search and analytical tools system with a cluster that uses cloud architecture for hosting.
You can focus on working with the service, enjoy all its benefits, and we will take care of the technical issues of cluster organization and its operation.
Our area of responsibility includes:
By default, automatic cluster backup is performed every 24 hours between 1:00 AM and 5:00 AM GMT+4. All indexes are saved during the backup. All backups are available for restoring within 7 days after creation.
The software in the OpenSearch project is released under the Apache 2.0 license, which gives permission to use the software freely. The client does not need to purchase a license.
Managed Service for OpenSearch is a distributed search and analytics suite that can be applied to on-premises, hybrid and multi-cloud environments across multiple providers. However, we believe that the use of our Managed Service for OpenSearch will be more effective if the data being searched and analyzed is stored on our cloud infrastructure.
Before upgrading OpenSearch version, we recommend that you check the OpenSearch version history on the vendor's official website and make sure that the new version will not affect your applications.
To test the new version of OpenSearch, it is recommended to create a backup copy of your cluster and create a test cluster with the new version of OpenSearch on its basis. After successful validation, you can upgrade the source cluster version.
In any case, it is recommended to create a backup of your cluster before upgrading the OpenSearch version, regardless of whether you plan to create a test cluster or not.
From OpenSearch's perspective, a document is a set of fields of the form: key and key value. The index stores the document in an optimized form to allow fast searching on the fields in the document.
If there are multiple hosts in a cluster, index sharding and replication becomes available.
Index sharding is an approach that involves dividing search engine indexes into independent segments, each managed by a separate server instance, usually hosted on a separate compute node. Sharding distributes the load on the cluster and improves cluster performance. If one shard fails, information on other shards will remain available.
Index replication in OpenSearch is the process of creating and maintaining exact copies of data indexes on multiple nodes in a cluster. Data writes and changes are performed only on the primary node, from which data changes are propagated to replica nodes. Reading can be performed from the primary nodes and their replicas. Due to this high availability of data and provides fault tolerance of the system. If one of the nodes fails, the rest of the replicas continue to serve requests. Index replication in OpenSearch helps to provide reliability and fault tolerance of the search and analytics system. The number of replica shards can be changed, but the number of primary shards is fixed when the index is created.
If you work in IT, the term “cloud” isn’t just a buzzword — it’s a powerful tool for storing and processing data.
PaaS (Platform as a Service) was initially designed as a solution for developers to build applications without dealing with server setup and infrastructure management.
TCP/IP is the backbone of everything. This protocol stack is like the circulatory system of the Internet and cloud computing.