Frequently Asked Questions

Do you support multi-tenancy?

Yes, StreamAnalytix has a concept of workspaces that can be leveraged for multi-tenancy. User activity in one workspace is isolated from other workspaces in the system.

Does the system support resource isolation?

Yes, the system allows resource isolation. During the creation of a new workspace, the administrator can allocate dedicated cluster nodes to that workspace which will not be shared by another workspace.

Do you support Apache Spark?

Currently, StreamAnalytix uses Apache Spark’s Streaming API. Support for Spark batch coming soon in Q1 2017.

Do you provide any dashboard/visualization tools?

Yes. StreamAnalytix has support for real-time dashboards and visualization.

Do you provide any monitoring capabilities for the real-time applications that are running on the cluster?

Yes. There is an entire section in StreamAnalytix that is created to monitor pipelines. The feature covers various aspects of monitoring of a pipeline and its components providing information on throughput, latency time, processing time etc. The system also supports configuring alerts on monitoring metrics.

Do you have support for analytical algorithms?

StreamAnalytix comes with a PMML processor, which can be used to execute a PMML model in the pipeline. This model is applied on every incoming event to evaluate the analytical algorithm defined within the PMML file.

My analytical algorithm needs to do lookups on historical user data. Do you support this?

Yes. StreamAnalytix supports a distributed cache that can be leveraged for holding meta information or any such shared data structure. You can also invoke custom lookups via the ‘Custom Processor’.

Can I execute my custom business logic in a pipeline?

Yes definitely. The best part of StreamAnalytix as a framework is the amount of flexibility it provides. You can write your own business logic and integrate it in the pipeline via the ‘Custom processor’.

What are the out of the box streaming connectors available?

StreamAnalytix currently supports RabbitMQ and Kafka connectors out of the box. Most of the streaming solutions need a queue to maintain a balance between the rate at which data is produced and the rate at which systems are able to process it. 

How can I connect to a streaming source other than the ones available out of the box?

We have provided a custom connector in addition to the out of the box connectors so that you can connect to virtually any source you want. All you need to do is implement an interface exposed by the platform for the specific source you want to connect to.

Can I stream data from files?

Yes. StreamAnalytix comes with an agent that can read data from files and push into StreamAnalytix via Kafka or RabbitMQ. You can run this agent on any machine from where you want to read the data and process it in StreamAnalytix.

What kind of streaming data is supported?

StreamAnalytix can process almost all kinds of data formats. It supports JSON, CSV and Regular expressions out of the box and for other formats, you can write your own parser to parse and process the incoming data.

Can I read from the start offset available for a Kafka Topic?

Yes. You can read from the start offset available for any Kafka Topic. While configuring the Kafka channel, you need to select the option for ‘forceFromStart’ as true. Every time you start the pipeline, the Kafka channel shall read the data from the earliest offset available within that topic.

What are the various NoSQL databases you support?

We support HBase and Cassandra NoSQL stores for persisting data.

What are the various Indexing frameworks you support?

We support Solr and ElasticSearch as the indexing frameworks.

Is it possible to ‘route’ messages to different operators based on some criteria?

Yes it is possible to route messages to different operators. We have an out of the box filter processor that can be used to apply the criteria and direct the messages to different operators.

Can I integrate multiple streaming pipelines?

Yes. You can use the sub-system integration feature to integrate multiple streaming pipelines.

Can I stream data to a web browser via websocket?

Yes. There is an out of the box streaming emitter that is bundled with StreamAnalytix that can be used to stream data to a web browser via websocket.

Do you support SockJS as the web sockets?

Yes, we support SockJS. If your websocket implementation leverages SockJS, you can consume data via the STOMP protocol over RabbitMQ and StreamAnalytix.

Do you support complex event processing like pattern detection or correlation of events from multiple sources?

We have an integrated CEP engine that allows us to perform complex event processing in real-time. The CEP engine enables us to correlate events from multiple sources and detect pattern amongst them. It also allows us to perform patter detection on a single source of data.

I want to calculate statistical functions over a moving window in real-time. Can this product help me?

Yes. You can apply statistical functions on a moving time window in real-time. There is an out of the box Statistical CEP processor that can be used to run statistical functions on both fixed and moving windows in real-time.

What is the installation process?

StreamAnalytix bundles its own ‘Cluster Provisioning and Deployment’ tool. This tool allows you to install the product along with its pre-requisites in simple and easy steps. A complete installation guide is available to walk you through the install process.

If I already have a Hadoop cluster, can I connect to it?

Yes.

If I already have a storm cluster, can I connect to it?

Yes.

If I already have a kafka cluster, can I connect to it?

Yes.

How do I migrate/move from pipeline from Dev to Production Environment?

StreamAnalytix is bundled with a very useful feature called import and export of pipelines. Once you test your pipelines on the development cluster you can export these pipelines by just a click of a button. These exported pipelines can then be imported into the destination environment without the need of building/configuring any of your pipeline.

Are you in the Cloud?

StreamAnalytix can be deployed in the cloud. For Enterprises having hybrid infrastructure with data on the cloud, StreamAnalytix supports data ingestion from / sink to cloud databases such as Amazon S3.

How is support provided?

Customer service is something we like to compete on. Support is offered to all the users through our Support website, as well as via email.

For commercial customers, we offer professional services, on-site customer training, implementations, and software customizations as per the requirements.

Does StreamAnalytix offer product training and demonstrations?

Yes, we do offer live demonstrations and product trainings. You can visit our website www.streamanalytix.com to request for a live demo.

Does StreamAnalytix have a professional services team?

Yes, we do offer professional services, on-site customer training, implementations, and software customizations to our customers.

Please feel free to contact us if your are looking for any assisted support or advisory services.

Is your product an Open Source software application?

No, StreamAnalytix is a proprietary software application but we make use of Open-Source technologies.

StreamAnalytix is an Enterprise grade product based on a proven, best-of-breed Open Source stack including Apache Spark, Apache Storm, and integrates seamlessly with popular Hadoop and NoSQL platforms.

Can I evaluate you product for free, before purchasing it?

Yes! You can evaluate our product for free, allowing you to see and use our software before purchasing. StreamAnalytix provides a fully functional version of the product for evaluation.

You can start a free evaluation here: http://streamanalytix.com/download

What benefit you provide over native Open Source?

As per our analysis, companies end up saving more than 25% by using StreamAnalytix over a period of 3 years as compared to building solutions in-house using native open source. Open source products are cheap (no license cost), but the total cost of ownership (which includes maintenance, support, etc) is higher. Apart from cost, there is an early-mover advantage as well.

Who are your competitors?

A lot of companies now want to add real-time data analytics capabilities to their Big Data architecture stack to gain from the data the moment it generates from a source. We make it extremely easy and fast for enterprises to go live with their real-time data analytics use-cases in a matter of days.

Who are your customers?

We have Fortune 500 companies from across the industries, mostly in telco, financial services, and technology companies.

Do you have specific vertical solutions?

StreamAnalytix has been used across industries for many use cases such as Internet of Things (IoT), sensor data analytics, e-Commerce and Internet advertising, security, fraud, insurance claim validation, credit-line management, call center analytics, and log analytics. It also enables enterprise IT and business transformation with horizontal capabilities like streaming ETL to speed up slow batch processes to near real-time.