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Today: Elastic NV (enterprise search)
Company description: Elastic is a search company. When you hail a ride home from work with Uber, Elastic helps power the systems that locate nearby riders and drivers. When you shop online at Walgreens, Elastic helps power finding the right products to add to your cart. When you look for a partner on Tinder, Elastic helps power the algorithms that guide you to a match. When you search across Adobe’s millions of assets, Elastic helps power finding the right photo, font, or color palette to complete your project.
As Sprint operates its nationwide network of mobile subscribers, Elastic helps power the logging of billions of events per day to track and manage website performance issues and network outages. As SoftBank monitors the usage of thousands of servers across its entire IT environment, Elastic helps power the processing of terabytes of daily data in real time.
In terms of offerings, Elastic delivers technology that enables users to search through massive amounts of structured and unstructured data for a wide range of consumer and enterprise applications. The company’s primary offering is the Elastic Stack, a powerful set of software products that ingest and store data from any source and in any format and perform search, analysis and visualization in milliseconds or less. The Elastic Stack is designed for direct use by developers to power a variety of use cases. Elastic has also built software solutions on the Elastic Stack that address a wide variety of use cases, including app search, site search, enterprise search, logging, metrics, APM, business analytics and security analytics. These products are used by individual developers and organizations of all sizes across a wide range of industries.
Elastic was founded in 2012 by Shay Banon, who currently serves as CEO, along with Steven Schuurman, Uri Boness and Simon Willnauer in Amsterdam. The company is distributed with offices all around the world. Elastic went public on the New York Stock Exchange in October 201 under the ESTC ticker.
Markets: Elastic’s products are used by companies in most industries, including technology, healthcare, financial services, government, telecom, media, retail, transportation and higher education.
International Operations: Elastic has offices and employees around the world, including Amsterdam, Austin, Berlin, Chicago, Copenhagen, Hong Kong, London, Munich, New York, Paris, Phoenix, San Francisco, Seoul, Singapore, Sydney, Tokyo and Washington, D.C. Elastic has customers in over 80 countries.
Product and Services
Elasticsearch is the heart of the Elastic Stack, where users store, search. analyze data.
Kibana is the user interface for the Elastic Stack. It allows users to manage the Elastic Stack and visualize data. Additionally, the user interfaces for many Elastic solutions are built into Kibana.
Beats and Logstash are data ingestion tools that enable users to collect and enrich any kind of data from any source for storage in Elasticsearch. Beats are lightweight agents purpose-built for collecting data on devices, servers and inside containers. Logstash is a dynamic data collection pipeline with an extensible plugin ecosystem.
Additionally, Elastic offers a series of solutions:
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App search. Elastic App Search includes a refined set of API clients for common programming frameworks to enable search of data stored in applications and has an intuitive interface to help tune search queries for optimal utility. |
The specialized website crawler built into Elastic Site Search enables anyone to easily add search to their website Elastic Site Search also offers an interface for search analytics and tuning relevance to match user behavior and expectations.
Search capabilities and simple APIs serve as the foundation for integrating connectors and crawlers for data sources commonly used by enterprises, such as shared drives and other collaboration and document sharing offerings.
Elastic APM includes agents for common programming frameworks and an APM Server designed for scalable collection and processing of metrics coming from APM agents. It includes an interface supporting custom visualizations for waterfall transactionviews and code-level visibility into application performance.
These solutions come with pre-built configurations making it easy to useBeats and Logstash to ingest the appropriate type of data. They also include default Kibana searches, dashboards and visualizations to deliver instant insights.
Key Features
Elasticsearch is a distributed search and analytics engine capable of solving a growing number of use cases. The heart of the Elastic Stack, it centrally stores data so users can discover the expected and uncover the unexpected. Elasticsearch enables users to perform and combine many types of searches — structured, unstructured, geo, metric. It’s one thing to find the 10 best documents to match a query. But how does someone make sense of, say, a billion log lines? Elasticsearch aggregations let users zoom out to explore trends and patterns in their data.
Kibana is a visualization tool to help users configure and manage all aspects of the Elastic Stack. Kibana core ships with histograms, line graphs, pie charts, sunbursts and more. Users can also use Vega grammar to design their own visualizations. All leverage the full aggregation capabilities of Elasticsearch.
Logstash is an open-source data collection engine with real-time pipelining capabilities. Logstash can dynamically unify data from disparate sources and normalize the data into destinations of a user’s choice.
While Logstash originally drove innovation in log collection, its capabilities extend well beyond that use case. Any type of event can be enriched and transformed with a broad array of input, filter and output plugins, with many native codecs further simplifying the ingestion process. Logstash accelerates insights by harnessing a greater volume and variety of data.
Beats is a platform for lightweight shippers that send data from edge machines to Logstash and Elasticsearch.
Insight and Analysis
Here is a professional’s review posted on IT Central Station in 2019:
Overall comment: “We use this solution to collect log data and analyze it. We have an on-premises deployment.”
What is most valuable? “The special text processing features in this solution are very important for me. As a system, it is easy to use.”
What needs improvement? “This is not a robust system, so in terms of resilience, they have to make some improvements. From time to time the system goes down and we have to start again, after adjusting some configuration parameters. Technical support can be improved. The interface would be improved with the inclusion of dashboards to assist in analyzing problems because it is very difficult. Better dashboards or a better configuration system would be very good.”
For how long have I used the solution? “I have been using this solution for six months.”
What do I think about the stability of the solution? “This is not exactly a stable solution, which is why we are considering another compatible tool, and whether we go on with Elasticsearch or change it.”
How are customer service and technical support? “I follow their forum and blogs, and I have also asked questions directly to their technical department. I would say that support is moderate. It is not very good or very bad, but in between.”
Which solution did I use previously, and why did I switch? “We did not use another solution prior to this one.”
How was the initial setup? “The initial setup of this solution is easy and straightforward. The deployment is both easy and quick.”
What about the implementation team? “We have an in-house team that handles deployment. Two people are enough for deployment and maintenance.”
What other advice do I have? “My advice for anybody considering this solution is that it is an easy to use tool, but for work that is not complex. If on the other hand, the work is more complex, with more data and perhaps a clustering environment, then they may have to consider something more stable and more robust. I would rate this solution a seven out of 10.”
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Here is a professional’s review posted on Gartner Peer Reviews in 2019:
Overall comment: “Elasticsearch, logstash, and kibana provide an excellent stack for log analysis, application monitoring, and much more. While you get most features on the free tier, the most important features are reserves for their paid tiers.”
Please explain the business problems or needs that prompted the purchase of this product or service. “Way too many websites to effectively look at logs during a time of duress on a server. The log analysis functionality has saved many many hours of effort in combing logs for potential issues.”
What do you like most about the product or service? “The flexibility of the elk stack is one of its greatest attributes. With the addition of beats you can write a plugin to basically do whatever you want.”
What do you dislike most about the product or service? “The pricing model is awful. They force you into a managed service and if you dont have 13K+ to spend you are SOL. In addition to the unfair pricing model, upgrades can be dicey. Configuration options that worked for years may break, new features may explode old features. They have upgrade assistants built in which helps, but the fact that they need to include upgrade assistants speaks for itself.”
If you could start over, what would your organization do differently? “Probably would back off on the roll out of the service given some of the core features we ended up needing were locked to high priced license tiers.”
What one piece of advice would you give other prospective customers? “Deeply consider Apache solr before diving into ELK. Consider the data you are planning to ingest, total size, how often it will get searched, etc., and plan your resources accordingly. Also the whole 3 node cluster, while elastic says it is best practice, is kinda false. It will run just fine on a single node for smaller workloads. We process about 20-50 GB of data a day and have had no instances of data loss caused by running on a single node. Obviously you will lose some data during upgrades but I am happy to pay that price over the cost of running 3+ nodes.”
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List of current customers: Microsoft, Netflix, Verizon, Airbus, Home Depot, Mayo Clinic, JPL NASA, eBay and the U.S. Census Bureau.
Delivery: The Elastic Stack and the Elastic solutions generally can be deployed on premises, in public or private clouds, or in hybrid environments, to satisfy various user and customer needs. Elastic’s goal is to ultimately offer all of its products as both self-managed and SaaS deployments.
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Self-managed. Elastic users can manage their own deployments of the Elastic Stack and Elastic solutions. To help with more complex deployment scenarios, Elastic offers Elastic Cloud Enterprise (ECE), a paid proprietary product, to deliver centralized provisioning, management and monitoring across multiple deployments. |
Elastic has developed a family of SaaS products called Elastic Cloud, including Elasticsearch Service, Elastic Site Search Service and Elastic App Search Service. Elastic hosts and manages its Elastic Cloud products on infrastructure from multiple public cloud providers, including Google Cloud, Alibaba and Tencent.
Pricing
Pricing info can be found here: https://www.elastic.co/products/elasticsearch/service/pricing. Elastic sales can also be reached at (650) 458-2625.
Other key players in this market:
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Contact information for potential customers: https://www.elastic.co/contact
800 West El Camino Real, Suite 350
Mountain View, Calif. 94040
General +1 650 458 2620
Sales +1 650 458 2625
info@elastic.co | sales@elastic.co
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