PageSourceSearch

https://www.kinetica.com/assets/10-reasons-why-kinetica-rocks-syvd2Rm5.js

js kinetica.com collected 2026-10-02 06:35:04 UTC 9,929 bytes, 35 lines download raw bytes

1const e="10-reasons-why-kinetica-rocks",a="10 Reasons Why Kinetica Rocks for Analytics",t="Today’s analytical workloads require faster query performance, advanced analysis methods, and more frequent data updates. Kinetica meets these needs with its GPU-accelerated analytical database for real-time insights on large and streaming datasets. We believe that there are still many people who might not know much about Kinetica. Are you one of them? Continue reading—there are at least 10 reasons why we think Kinetica will rock your analytical workloads. 1. The GPU is your new friend Analytical data systems face several challenges. First, the explosive growth of data has created truly giant datasets, and second, there is a lack of computational capacity to process these massive data sets. So why should you depend only on your CPU?  Kinetica is built from the ground up to harness the parallel processing power of the GPU and multi-core devices using vectorized memory structures and SIMD processing. 2. You’re a data scientist? No problem, we’ve got you covered With Kinetica, you can create killer visual analytical dashboards—easy, fast, and out-of-the- box. Kinetica “Reveal” […]",i="2017-12-01",n="Dipti Borkar",s="https://kinetica-web-assets.s3.us-east-1.amazonaws.com/assets/blog/firestations2.gif",o=[],r=`<p class="text-gray-600 leading-relaxed mb-4">Today's analytical workloads require faster query performance, advanced analysis methods, and more frequent data updates. Kinetica meets these needs with its GPU-accelerated analytical database for real-time insights on large and streaming datasets.</p>
2<p class="text-gray-600 leading-relaxed mb-4">We believe that there are still many people who might not know much about Kinetica. Are you one of them? Continue reading—there are at least 10 reasons why we think Kinetica will rock your analytical workloads.</p>
3
4<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">1. The GPU is your new friend</h2>
5<p class="text-gray-600 leading-relaxed mb-4">Analytical data systems face several challenges. First, the explosive growth of data has created truly giant datasets, and second, there is a lack of computational capacity to process these massive data sets. So why should you depend only on your CPU? Kinetica is built from the ground up to harness the parallel processing power of the GPU and multi-core devices using vectorized memory structures and <a href="https://en.wikipedia.org/wiki/SIMD" class="text-kinetica-600 hover:underline">SIMD</a> processing.</p>
6
7<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">2. You're a data scientist? No problem, we've got you covered</h2>
8<p class="text-gray-600 leading-relaxed mb-4">With Kinetica, you can create killer visual analytical dashboards—easy, fast, and out-of-the-box. Kinetica "<a href="/product/reveal/" class="text-kinetica-600 hover:underline">Reveal</a>" is a web-based visualization framework that makes it easy to slice, dice, visualize, and interact with data in Kinetica. Reveal provides on-the-fly data analytics and real-time data discovery using easy-to-use drag-and-drop widgets. Reveal accelerates the rendering of charts, maps, and additional data elements by leveraging the GPU. Still need interactive queries on the dataset? Don't worry—check out the SQL query editor.</p>
9
10<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">3. Scale linearly, without falling apart</h2>
11<p class="text-gray-600 leading-relaxed mb-4">Kinetica runs on industry-standard hardware, equipped with GPUs. The GPU delivers almost linear scalability, so you can perform real-time analytics on large datasets, with predictable hardware demands. You can scale horizontally simply by adding additional nodes to distribute the data. This can be combined with scaling up at any time to increase memory capacity and processing power. Sharding of data can be done automatically, or specified and optimized by the user.</p>
12
13<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">4. Nimbly handle in-memory data processing</h2>
14<p class="text-gray-600 leading-relaxed mb-4">Compared to some of the most advanced CPU-based in-memory systems, Kinetica can ingest and process data in-memory at high speeds, delivering 10-100x acceleration. But, if your database must be fast, holding data in memory itself is insufficient, because compute resources can quickly become a bottleneck. The GPU can solve this. For example, on a star schema, with fact tables of 150 billion rows connected with multiple dimension tables in a classic distributed JOIN with GROUP BYs, Kinetica can deliver 10-100x better performance with only 1/10th of the hardware.</p>
15
16<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">5. Use the query language you love – SQL</h2>
17<p class="text-gray-600 leading-relaxed mb-4">Everyone—including us—loves the <a href="/docs/concepts/sql.html" class="text-kinetica-600 hover:underline">SQL</a> query language. Kinetica has a high-speed query execution engine that leverages GPU acceleration to deliver blazingly fast queries. In contrast with other GPU-based database systems, Kinetica offers full JOIN supp
17ort with left, right, outer, and inner JOINS across many columns and tables. Kinetica also provides full SQL-92 query support through certified JDBC and ODBC connectors, making it painless to swap in Kinetica as a replacement data source for faster, accelerated analytics.</p>
18
19<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">6. Continue your love affair with popular BI and other ecosystem tools</h2>
20<p class="text-gray-600 leading-relaxed mb-4">We get it. Sometimes you just cannot throw away the BI investments you've already made. The good news is that Kinetica plugs right into your ecosystem and supports a variety of different <a href="/docs/connectors/index.html" class="text-kinetica-600 hover:underline">connectors</a> with other tools. You can connect Kinetica to Apache Hadoop, NiFi, Spark and Spark Streaming, Storm, and Kafka, and other commercial tools such as <a href="/blog/choosing-gpu-analytics-database/partner/fme/" class="text-kinetica-600 hover:underline">FME</a>.</p>
21<p class="text-gray-600 leading-relaxed mb-4">
21Kinetica can also be connected to popular BI tools such as <a href="/blog/choosing-gpu-analytics-database/partner/tableau/" class="text-kinetica-600 hover:underline">Tableau</a>, MicroStrategy, and <a href="/blog/choosing-gpu-analytics-database/partner/powerbi/" class="text-kinetica-600 hover:underline">Power BI</a> through ODBC/JDBC connectors. Can't find a connector you love? Don't forget that you can also take advantage of the native <a href="/docs/api/rest/index.html" class="text-kinetica-600 hover:underline">REST API</a> for integration.</p>
22
23<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">7. Build richer analytical applications with geospatial and full-text search</h2>
24<p class="text-gray-600 leading-relaxed mb-4">Want to build richer, more intelligent analytical applications? Kinetica provides a built-in geometry engine that combines native geospatial functionality, filtering, and GPU acceleration to work in modern analytical applications where time and location matter. With Kinetica's natural language processing (NLP), you can select which string columns in the table that you want to search.</p>
25
26<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">8. High availability</h2>
27<p class="text-gray-600 leading-relaxed mb-4"><a href="/blog/choosing-gpu-analytics-database/docs/ha/index.html" class="text-kinetica-600 hover:underline">Kinetica offers Active/Active HA</a> and automatic replication between clusters. This eliminates a single point of failure in a given cluster and provides reliable and fast recovery from failure. If a node fails, the database continues to work meeting high-nines of availability. Patches and upgrades can happen in parallel, while concurrent sessions are hitting the system during peak hours!</p>
28
29<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">9. Enterprise-grade security</h2>
30<p class="text-gray-600 leading-relaxed mb-4">It goes without saying that security is an important part of any modern database platform. From the very start, Kinetica has security in its DNA, offering rich security controls including authentication, authorization, and encryption to meet your security and compliance needs.</p>
31
32<h2 class="text-2xl font-bold text-gray-900 mt-8 mb-4">10. Outstanding support and documentation</h2>
33<p class="text-gray-600 leading-relaxed mb-4">With Kinetica, we've got you covered, and you are never alone. We provide our customers with mission-critical <a href="/support/" class="text-kinetica-600 hover:underline">support</a> to get you up and running in production without any hiccups.</p>
34<p class="text-gray-600 leading-relaxed mb-4">Getting started with Kinetica is easy with our Quick Start <a href="/quickstart/" class="text-kinetica-600 hover:underline">guides</a>. They will take you from knowing relatively little about Kinetica to having a good grasp of the fundamentals. If you want to dive deeper, check out the <a href="/docs/" class="text-kinetica-600 hover:underline">documentation</a> to get more details around installation, configuration, concepts, and APIs.</p>
35<p class="text-gray-600 leading-relaxed mb-4">We'd love to hear about your Kinetica experiences, and if you have any questions, reach out to us via the <a href="/forum/" class="text-kinetica-600 hover:underline">forums</a> and one of our experts will get back to you. Why are you waiting? Take Kinetica for a <a href="/trial/" class="text-kinetica-600 hover:underline">test drive today</a>, and get started building your apps with Kinetica.</p>`,l={slug:e,title:a,excerpt:t,date:i,author:n,featuredImage:s,categories:o,body:r};export{n as author,r as body,o as categories,i as date,l as default,t as excerpt,s as featuredImage,e as slug,a as title};

Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.