What data sources are currently supported?

Kyligence Cloud supports various object storages on the cloud, such as AWS S3, Azure Blob Storage, Azure Data Lake Storage, HUAWEI CLOUD OBS, etc. Users can store their data files as CSV, parquet, or ORC format files on the object storage, through Kyligence Cloud's OLAP analysis engine, you can analyze data directly.

In addition, we also support native data warehouses on the cloud as data sources, such as Azure Synapse, Snowflake, etc.

What common BI tools does Kyligence Cloud support?

Kyligence Cloud supports mainstream BIs such as Tableau, Excel, Power BI, MicroStrategy, Qlik, Obiee, FineBI, etc. In addition, Kyligence Cloud not only has the built-in BI (Kyligence Insight), but also provides rich APIs (REST API, JDBC, and ODBC), and XMLA/MDX to integrate with third-party BI tools.

What third-party user authentication systems can Kyligence Cloud connect to?

Kyligence Cloud not only provides a built-in user system, but can also be integrated with a variety of third-party user authentication systems, such as LDAP, Azure Active Directory, etc.

Kyligence Cloud can also support the hybrid mode, which enables the built-in user system and the third-party system at the same time. Users can use the built-in user system as a service account.

How does Kyligence Cloud accelerate queries?

Kyligence Cloud has a built-in OLAP engine based on machine learning AI. Using precomputation technology, users can create a multi-dimensional model and build the accelerated indexes on the model. The accelerated indexes will be stored on the object storage. When a user queries the data, if there are accelerated indexes, the query can be quickly answered through the accelerated indexes. If there is no accelerated index, the query engine will concurrently query the data source to answer the query.

How do I create a model in Kyligence Cloud?

If the user is a data analyst with OLAP analysis experience, the user can manually create a multi-dimensional model based on the data source; if the user has no experience about modeling, he can upload SQL (such as querying historical SQL) through the automatic modeling function provided by Kyligence Cloud. The system can create a multi-dimensional model automatically.

Regardless of whether you use manual modeling or automatic modeling, the model has the ability of self-optimizing. With the query requests coming in, the system will recommend the optimized accelerated indexes for the model.

How does Kyligence Cloud build an accelerated index?

After a model is created, the user can load data on this model, the accelerated indexes will be built while loading data. Kyligence Cloud divides the accelerated indexes into one or more continuous segments in the time dimension on the model. When a user submits a build job, the model will automatically generate a segment. When the build job is successfully completed, the index files of the segment will be stored on the object storage.

After a build job is submitted, the system will detect how much computing resources are needed for the build job by an AI-based algorithm. The system will scale up the computing resources for this build job. When the build job is completed, the computing resources will be automatically scaled down to improve the efficiency and utilization of resources.

What are the advantages of Kyligence Cloud compared to other data warehouses on the cloud such as AWS Redshift and Azure SQL DW?

From the perspective of technical architecture, Redshift and SQL DW are both parallel distributed computing database architectures based on the MPP engine. For Kyligence Cloud, its bottom layer relies on the capabilities of cloud data lake storage and distributed pre-computation engines. It can theoretically achieve unlimited performance expansion capabilities; Redshift and SQL DW will support limited concurrency. In some scenarios with large data volume and high concurrency, Kyligence Cloud will have better performance and lower TCO. In addition, Kyligence Cloud also supports auto-scaling of computing resources based on the workload of tasks to help users improve resource utilization.

From the perspective of the capabilities provided by the product, Kyligence Cloud provides a unified semantic layer based on MDX to simplify data insight, which is currently not available in other products.

What is the difference between Kyligence Cloud and SSAS?

SSAS is Microsoft's data analysis service, divided into a local version and a cloud version. The cloud version is called AAS. Both are tools for data modeling based on OLAP modeling theory. AAS uses a memory-based MPP query engine. With the cloud version, there are some limitations on scalability. The maximum number of nodes for expansion is 8 units. Each node is limited by the size of physical memory, and it's easy to reach the upper limit for concurrency.

What is the difference between Kyligence and the open source Apache Kylin?

Apache Kylin is the leading open source OLAP engine for big data. Kyligence Cloud is an Intelligent OLAP Platform that is powered by an engine based on Apache Kylin. In addition to the OLAP engine, Kyligence Cloud provides other advanced analytics features, such as AI-Augmented optimization, seamless integration with mainstream BI tools and commercial SLA support. Learn more by taking a look at the Apache Kylin vs Kyligence Fact Sheet.

How to migrate from Apache Kylin to Kyligence Cloud?

Kyligence Cloud supports the migration from Apache Kylin. Users can contact Kyligence's technical support team. We provide a unified and complete data cloud solution based on the user's data scale, data situation, and data platform construction.

How does Kyligence Cloud charge?

Kyligence Cloud charges customers for an annual subscription license. The license will not be tied to cloud resources and needs to be purchased separately.

For cost estimation, please refer to the Subscription Fee chapter in Kyligence Cloud user manual.

Does Kyligence provide technical support?

Kyligence provides 7/24 professional technical support for all Kyligence products. At the same time, Kyligence also delivers professional cloud solutions tailored based on a company's existing architecture, data volume, data sources, use cases, etc. These solutions empower companies with end-to-end services, including consulting, implementation, managed, and optimization services.

For details on technical support, please refer to the Tech Support chapter in Kyligence Cloud user manual.

How do I deploy Kyligence Cloud?

Kyligence Cloud supports to operate on Microsoft Azure, AWS, Google Cloud, or HUAWEI CLOUD. There are currently three methods to deploy Kyligence Cloud on supported cloud platforms:

For more information about how to deploy Kyligence Cloud, please refer to the Deployment and Uninstall chapter in Kyligence Cloud user manual.

What are the resources required before deploying Kyligence Cloud?

Before deploying Kyligence Cloud, you need to prepare a cloud account on a supported public cloud platform (Microsoft Azure, AWS, Google Cloud, or HUAWEI CLOUD).

Resources needed: at least 150 vCores and 600 GB memory in your cloud account.

For more information about required cloud resources, see below:

Does Kyligence Cloud support Azure's HDI platform?

Kyligence Cloud does not use Hadoop, so there is no requirment for the Azure HDI platform as long as the user has necessary resources (VM, Network Interface, Object Storage, Load Balance, etc.) under the subscription.

What deployment mode does Kyligence Cloud support?

As a PaaS offering, Kyligence Cloud supports public cloud and private cloud. The application will be deployed under the user's cloud subscription and use the resources in the subscription. The data is stored in the user's cloud subscription, and Kyligence will not access any of the user's data.

How and who will manage the computing resources of Kyligence Cloud?

Kyligence Cloud uses a VM based Spark Standalone cluster as the computing cluster, and computing tasks are scheduled by the Spark Master node. Kyligence will automatically manage the Spark cluster.

Does Kyligence Cloud support MDX?

Kyligence Cloud provides the Kyligence MDX application, which users can install in Kyligence Cloud with one click. With Kyligence MDX installed, users can connect Excel to Kyligence Cloud to analyze cloud data.

On how to install Kyligence MDX, please refer to the Kyligence Application chapter in Kyligence Cloud user manual.

Copyright © Kyligence Inc. all right reserved,powered by GitbookLast Modified: 2022-07-19 17:20:22

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