Upgrade your data analytics with our Managed Service for Elasticsearch in the cloud. Enjoy automatic scaling, high availability and seamless integration with cloud services for efficient processing, search and analysis of your information.
Elasticsearch provides efficient storage and fast access to logs, enabling you to analyze them and extract valuable insights. It also offers powerful search and aggregation tools for analytics such as monitoring, error tracking, and user‑behavior analysis.
Elasticsearch is a powerful search platform offering full‑text search, filtering, and data aggregation. It efficiently indexes and processes large text volumes and supports keyword, phrase, prefix, and complex boolean queries and filters.
Elasticsearch can collect and analyze monitoring data from multiple sources, allowing you to track system health in real time, check performance, and detect issues to optimize operations.
The Managed Service for Elasticsearch frees developers from handling backups, logging, monitoring, scaling, hardware tuning, and software patching, so they can focus on delivering high‑quality applications.
Data is encrypted at rest and in transit, protecting it from unauthorized access. You can also use your own encryption key for an extra layer of control.
The service’s serverless architecture lets you scale disk space and RAM to match workload demands, ensuring high performance and efficient resource use.
Fully compatible with the Elasticsearch API and a wide range of data formats and clients, making migration seamless with little or no code changes.
DBaaS (Database as a Service) is a cloud-based approach to data storage and management in which you no longer need to install or maintain the database yourself. Instead, you receive a ready-to-use, fully optimised cloud solution that delivers high availability, effortless scalability, and comprehensive database management.
A high-performance NoSQL database ideal for flexible, efficient management of large volumes of data.
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A massively parallel processing (MPP) platform for large-scale data warehousing and analytics.
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A massively parallel processing (MPP) platform for large-scale data warehousing and analytics.
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The world’s most popular open-source database, renowned for its reliability, simplicity and speed.
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An in-memory data-structure store that serves as a database, cache and message broker for lightning-fast data access.
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A distributed data-streaming platform that lets you build data pipelines and real-time applications.
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A high-performance columnar DBMS optimised for online analytical processing (OLAP).
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An open search-and-analytics suite used for real-time log monitoring and analysis.
DiscoverHave a complex setup or additional pricing questions? Contact our sales team to get the information you need.
Your needs define our cloud, which adapts and scales to your workloads. Start with a small virtual machine and effortlessly grow into high‑load infrastructures with clusters, load balancers, and other tools.
Deploy virtual machines, configure networks and complex network architectures, manage data storage with great flexibility, and achieve high availability using load balancers and clusters. All of this — in an intuitive interface. With it, you can focus on what matters most — your business and ideas.
If you need maximum performance and control, we offer you the option of deploying OpenStack on Bare Metal. It is the key solution for high‑performance computing, big data processing, and situations where direct access to hardware resources is required.
An orchestration system that automates the deployment, scaling and management of containerised applications.
TryScalable, flexible and easy-to-manage storage for all kinds of data and workloads.
TryWhat tasks can Elasticsearch be used for?
Elasticsearch is a highly scalable distributed search engine for full-text search and data analysis with a web interface that can help you quickly find information in a large data set, for example, from a document in a corporate system to a product on a marketplace.
Elasticsearch is able to store a huge array of data and search through it.
Elasticsearch can be suitable for the following application scenarios:
Elasticsearch is suitable for organizing full-text search, both by separately specified criteria and fuzzy search. This solution is especially relevant for organizing searches among a large number of products and items, for example, for e-commerce: online stores, online pharmacies, marketplaces. An example of using Elasticsearch is the online store and catalog of Leroy Merlin products.
Since Elasticsearch is a non-relational storage of unstructured documents, it is perfect for organizing messaging systems. For example, Netflix and Tinder messaging systems are organized on Elasticsearch.
Elasticsearch allows you to store and process any data, logs, logs, system data, database analytics. Based on this data, you can build reports, dashboards, track business metrics, and customize alerts. An example is Airbus, which organized its document storage system on Elasticsearch.
What tasks does the Elasticsearch database management service provider take on?
Managed Service for Elasticsearch - provides a ready-to-use Elasticsearch search engine with a cluster hosted in the cloud.
You can focus on working with the system, enjoy all its benefits, and we will take care of the technical issues of organizing the database cluster and its operation.
Our area of responsibility includes:
How is the backup of database clusters organized?
By default, the cluster is automatically backed up every hour with all indexes saved. All backups are available for restoring within 7 days after creation.
Can I upgrade or downgrade my Elasticsearch cluster without losing data? Install updates to fix bugs and vulnerabilities?
Yes, you can upgrade the cluster version, but downgrading the version cannot be done. There are limitations for version upgrades, so you cannot upgrade a major version of the cluster, for example, from V7.X to V8.X.
However, you can always create a new cluster with the version you need and migrate data from the original cluster to it, and after successful data migration you can abandon the original cluster.
You do not need to install updates containing only bug and vulnerability fixes (maintenance release) yourself; we will do it, notifying you in advance about the timing and availability of the databases.
How long does it take to upgrade a version of an Elasticsearch cluster?
The time it takes to upgrade is determined by the structure and volume of data, as well as the configuration of your cluster. On average, a version upgrade takes about 1 hour.
Will the service be affected when performing a version upgrade of an Elasticsearch cluster?
When you upgrade an Elasticsearch cluster, you can still read data from or write data to the cluster, but you cannot make other changes.
We recommend that you perform version upgrades after hours or during times of minimal load on the cluster.
What is an index in Elasticsearch?
From Elasticsearch's point of view, a document is a set of fields, where each field is a pair of "key": "value". An index stores the data of these fields in the document in an optimized form to enable fast search on the fields in the document.