ELASTICSEARCH DEVELOPMENT COMPANY

Power your data search and analytics with Elasticsearch and nearshore talent.

We quickly assemble skilled teams to implement scalable Elasticsearch solutions that enable fast, accurate, and real-time data retrieval across large datasets.

elasticsearch development

+200 companies rely on

our 1% Top Talent

Elasticsearch Development Services We Provide

We offer a wide range of Elasticsearch development services, from custom search engine development to data analytics and integration. Explore our key offerings below:

Custom Search Engine Development

We build tailored search solutions using Elasticsearch to deliver fast, accurate, and scalable search functionality. Our custom search engines are optimized for performance, helping users find relevant data across large databases in real-time.

Data Analytics with Elasticsearch

We develop data analytics platforms powered by Elasticsearch, enabling real-time insights from large datasets. With Elasticsearch’s powerful aggregation features, we create dashboards and reporting tools that provide valuable insights from your data.

Elasticsearch Cluster Setup and Scaling

Our team sets up and configures Elasticsearch clusters to ensure your search and analytics applications are scalable and performant. We design clusters that handle high data volumes and traffic loads, ensuring fast data retrieval and fault tolerance.

Elasticsearch Integration with Existing Systems

We integrate Elasticsearch into your existing infrastructure, connecting it with databases, third-party services, and other data sources. This allows you to unify your data and leverage Elasticsearch’s capabilities for real-time search and analytics.

Log and Event Data Management with ELK Stack

We implement Elasticsearch, Logstash, and Kibana (ELK Stack) solutions to help you manage, analyze, and visualize log and event data. Our ELK solutions are ideal for monitoring systems, tracking performance, and gaining insights from large volumes of log data.

Elasticsearch Maintenance and Optimization

Our ongoing support services ensure that your Elasticsearch clusters remain optimized, secure, and up-to-date. We monitor performance, manage updates, and troubleshoot issues to ensure smooth operation and scalability as your data grows.

Why Choose Xpertsoft for Elasticsearch Development

Nearshore Expertise

Our developers are primarily based in Portugal, ensuring seamless collaboration with EU-based clients. With real-time communication and bilingual professionals, we offer efficient Elasticsearch development and support services.

Broad Technical Expertise

Beyond Elasticsearch, our team brings expertise in data analytics, search optimization, distributed systems, and cloud-based solutions. We deliver end-to-end services that ensure your Elasticsearch implementation is scalable, secure, and optimized for performance.

Tailored Elasticsearch Solutions

We provide flexible Elasticsearch development services that align with your business goals. Whether you need a custom search engine, data analytics platform, or log management solution, we tailor our services to meet your specific requirements.

The Elasticsearch Ecosystem We Used in Previous Work

Search and Analytics Solutions

Leverage Elasticsearch and its ecosystem to build high-performance search engines and analytics platforms:

  • Elasticsearch (for real-time search and analytics across large datasets)
  • Kibana (for data visualization and dashboards)
  • Logstash (for data collection, parsing, and transformation)
  • Beats (for lightweight data shipping from servers to Elasticsearch)
  • ElastAlert (for real-time alerting based on Elasticsearch data)

Data Integration and Processing

Integrate Elasticsearch with your existing infrastructure and handle large-scale data processing:

  • Logstash (for log aggregation and data transformation)
  • Kafka (for real-time data streaming and integration)
  • AWS Lambda (for serverless processing of search and analytics queries)
  • RabbitMQ (for messaging and data pipelines in distributed systems)

Cluster Management and Optimization

Ensure secure, scalable, and optimized Elasticsearch clusters with these tools:

  • Elastic Cloud (for cloud-based Elasticsearch management and scaling)
  • Kubernetes (for orchestrating Elasticsearch clusters in containers)
  • Docker (for containerized Elasticsearch deployments)
  • Prometheus and Grafana (for monitoring Elasticsearch cluster performance)
  • Shield (X-Pack) (for securing Elasticsearch clusters with authentication and encryption)

Accelerate your roadmap with an experienced Elasticsearch development company.

Key Facts to Know About Elasticsearch Development

  • Benefits of using Elasticsearch
  • 1. Fast, Real-Time Search and Analytics

    Elasticsearch is designed for fast, real-time search and analytics across massive datasets. Its distributed nature allows for quick data retrieval and processing, making it ideal for high-traffic applications, content management systems, and real-time monitoring.

    2. Scalable and Distributed Architecture

    Elasticsearch’s distributed architecture ensures that your search and analytics solutions can scale with your data. It supports horizontal scaling, allowing you to add more nodes as your data grows, ensuring optimal performance under heavy workloads.

    3. Powerful Full-Text Search Capabilities

    Elasticsearch offers advanced full-text search features such as fuzzy matching, autocomplete, and proximity search. These features enable users to find relevant data quickly, even with incomplete or approximate queries.

  • Elasticsearch is primarily used for
  • Elasticsearch is primarily used for building high-performance search engines, data analytics platforms, and log management systems. It is widely adopted for applications that require real-time data retrieval, monitoring, and analysis.

  • Reasons for Elasticsearch's popularity
    • Real-Time Data Aggregation: Elasticsearch provides powerful aggregation capabilities that allow businesses to analyze large datasets and create meaningful visualizations and reports in real-time.
    • Highly Customizable Search Functionality: Elasticsearch’s query DSL (domain-specific language) allows for fine-tuned control over search operations, enabling custom search functions such as filtering, faceting, and ranking.
    • Seamless Integration with the ELK Stack: Elasticsearch, Logstash, and Kibana (ELK) work together seamlessly to provide comprehensive data ingestion, search, and visualization capabilities for monitoring and log management.
    • Strong Community and Ecosystem: Elasticsearch has a large and active community that contributes to its growing ecosystem of plugins and tools, making it easier to extend functionality and integrate with other platforms.
    • Cost-Effective for Large-Scale Search Applications: Elasticsearch’s scalability and open-source nature make it a cost-effective solution for businesses that need to handle large volumes of data and offer high-speed search functionalities.
    • Multi-Language Support: Elasticsearch supports multiple languages, allowing businesses to create search applications for global audiences with language-specific text analysis and relevance scoring.
    • Cloud and On-Premise Flexibility: Elasticsearch can be deployed on cloud platforms like AWS, Google Cloud, and Azure or run on-premises, giving businesses flexibility in managing their infrastructure.

  • Useful Links

1. Fast, Real-Time Search and Analytics

Elasticsearch is designed for fast, real-time search and analytics across massive datasets. Its distributed nature allows for quick data retrieval and processing, making it ideal for high-traffic applications, content management systems, and real-time monitoring.

2. Scalable and Distributed Architecture

Elasticsearch’s distributed architecture ensures that your search and analytics solutions can scale with your data. It supports horizontal scaling, allowing you to add more nodes as your data grows, ensuring optimal performance under heavy workloads.

3. Powerful Full-Text Search Capabilities

Elasticsearch offers advanced full-text search features such as fuzzy matching, autocomplete, and proximity search. These features enable users to find relevant data quickly, even with incomplete or approximate queries.

Elasticsearch is primarily used for building high-performance search engines, data analytics platforms, and log management systems. It is widely adopted for applications that require real-time data retrieval, monitoring, and analysis.

  • Real-Time Data Aggregation: Elasticsearch provides powerful aggregation capabilities that allow businesses to analyze large datasets and create meaningful visualizations and reports in real-time.
  • Highly Customizable Search Functionality: Elasticsearch’s query DSL (domain-specific language) allows for fine-tuned control over search operations, enabling custom search functions such as filtering, faceting, and ranking.
  • Seamless Integration with the ELK Stack: Elasticsearch, Logstash, and Kibana (ELK) work together seamlessly to provide comprehensive data ingestion, search, and visualization capabilities for monitoring and log management.
  • Strong Community and Ecosystem: Elasticsearch has a large and active community that contributes to its growing ecosystem of plugins and tools, making it easier to extend functionality and integrate with other platforms.
  • Cost-Effective for Large-Scale Search Applications: Elasticsearch’s scalability and open-source nature make it a cost-effective solution for businesses that need to handle large volumes of data and offer high-speed search functionalities.
  • Multi-Language Support: Elasticsearch supports multiple languages, allowing businesses to create search applications for global audiences with language-specific text analysis and relevance scoring.
  • Cloud and On-Premise Flexibility: Elasticsearch can be deployed on cloud platforms like AWS, Google Cloud, and Azure or run on-premises, giving businesses flexibility in managing their infrastructure.

Add top 1% devs to
your in-house teams

Tap into the expertise of our top 1%  developers. Staff augmentation lets you boost your in-house teams with specialized experts. Expedite timelines without sacrificing output quality.

Here’s how we augment your team

STEP 1

Discovery Call

Share your requirements, budget, and necessary skill sets. We will draft a working timeline and select top developers for your team.

STEP 2

Assembling Your Team

Withindays, we’ll find suitable developers that fit your requirements. We ensure they have the right technical expertise and would be a great cultural fit for your team.

STEP 3

Onboarding and Scaling

After onboarding them, our developers will integrate with your team. Scale your engagement as needed – we’re happy to accommodate your demands.

Get an
entire Team

Looking to bring on more than just a few .NET developers? We’ll assemble a complete crew to support you. Whether it’s full-cycle front and back-end web development, QA, DevOps, UX/UI, or something else. Monitor the team’s performance and manage them as you see fit.

Here’s how you can get a dedicated team

nearshoring a development team

STEP 1

Discovery Call

We’ll learn about your business, organization structure, objectives, budget, timelines, and resource requirements. Then, we can start identifying the ideal talent for you.

STEP 2

Team Assembly and Integration

Once we assemble your dedicated team, we’ll ensure a smooth transition as they integrate with your organization.

STEP 3

Project Kickoff

After onboarding, your team is at your disposal. You’ve now acquired the resources you need without the hassle and high cost that usually comes with recruitment

Looking for Elasticsearch development at your organization?

See how we can help.