GridGain Solutions for SaaS Enablement

This article is the sixth and last in an editorial series with a goal to provide direction for SaaS company thought leaders on ways to achieve higher levels of scalability and performance through use of in-memory computing technology.

In last week’s article, we reviewed the customer decision points for selecting in-memory computing. The complete insideAI News Guide to Hyperscaling Your SaaS Infrastructure is available for download from the insideAI News White Paper Library.

GridGain Solutions for SaaS Enablement

In this segment, we’ll focus on the GridGain In-Memory Data Fabric and how its breadth of features represent a sound foundation for building a robust SaaS architecture. The GridGain In-Memory Data Fabric is built on top of an open source, incubating Apache project—Apache IgniteTM (incubating)—and is designed as an enterprise-grade data access and processing solution on-premises and in the cloud for today’s world of Fast Data.

Running in any public, private or hybrid cloud environment, the GridGain In-Memory Data Fabric enables definitive performance and scale for any Java, .Net or C++ application, including the most mission-critical workloads. Whether you are a “born-in-the-cloud” SaaS provider determined to accelerate time to market for your next hyperscale application, an ISV looking to add “as a service” capabilities to your existing software solutions, or an enterprise delivering internal, on-premises software as a service to your growing user base, chances are you’ll have the following concerns:

• Quickly and seamlessly adding users to your application
• Meeting or exceeding aggressive SLA provisions
• Improving application performance by orders of magnitude
• Seamlessly scaling up or scaling out on cost-effective commodity hardware
• Providing secure, multi-tenant access to your data
• Minimizing the amount of rework to application code and databases you are already invested in

PaaS for SaaS Providers

The GridGain In-Memory Data Fabric is a proven software solution which delivers unprecedented speed and unlimited scale to accelerate the growth of a SaaS business and enables high-performance transactions, real-time streaming and fast analytics in a single, comprehensive data access and processing layer. Here is a short list of motivations for choosing GridGain for your SaaS business:

• If your plan is to run your high-performance SaaS business in your own cloud infrastructure, or if you are looking for ways to optimize performance and reach of your SaaS offerings on the infrastructure of your cloud provider of choice.
• If you are a cloud provider looking to include PaaS capabilities that allow your customers to rapidly migrate or build their high performance, hyperscale SaaS offerings to your platform.
• If you need an easy, flexible and virtually unlimited way to scale different types of analytical, transactional or hybrid applications in a multi-tenant environment.

SaaS for the Real-Time Enterprise

For IT organizations wishing to transform into a service provider for their enterprise, creating the ability to rapidly and flexibly deliver internal software as a service to critical lines of business, the GridGain In-Memory Data Fabric offers a strategic approach to in-memory computing that delivers performance, scale and comprehensive capabilities far above and beyond traditional disk-based or even in-memory-enhanced databases, data grids or other in-memory-based point solutions. It offers a secure, highly available and manageable data environment that allows companies large and small to process full ACID transactions and generate valuable insights from real-time, interactive and batch queries.

DATA FABRIC FEATURE: In-Memory Data Grid

With its In-Memory Data Fabric, GridGain offers industry leading data grid functionality characterized by the fact that data are stored in-memory as opposed to traditional DBMS software that utilizes disk as the primary storage mechanism. By utilizing system memory rather than spinning disk, data grids are typically orders of magnitude faster than traditional DBMS systems. The GridGain data grid feature supports standard SQL for querying in-memory data including support for distributed SQL joins.

In direct response to the typical SaaS company’s requirements for unlimited growth, GridGain’s data grid feature contains an impressive feature set including advanced security, fault tolerance, topology resolutions, load balancing, collision resolutions, connected jobs, local node storage and much more. In a clustered in-memory solution like GridGain’s, the collection of all individual node memory can be used as a single, expansive “fabric” of virtually connected memory. Large data sets can be effectively partitioned across all nodes for high-end scalability, and computations can be intelligently parallelized for optimal processing speed.

At a fundamental level, GridGain enables promoting data up from residing in slow mechanical storage systems to fast memory. GridGain’s data grid feature solves many critical SaaS pain-points at once:

• Performance
• Scalability
• High availability
• Data consistency and reliability
• Detailed insight and management

DATA FABRIC FEATURE: In-Memory Compute Grid

Besides the data grid capability, the GridGain In-Memory Data Fabric also includes an In-Memory Compute Grid, which provides the means for parallel, in-memory processing of CPU-intensive or other resource-intensive tasks, including traditional High Performance Computing (HPC) and Massively Parallel Processing (MPP).

DATA FABRIC FEATURE: Real-time Streaming

To address the needs of many Saas applications for which traditional processing methods and disk-based storages, like databases or file systems, fall short—the GridGain In-Memory Data Fabric offers stream-processing capabilities. In-memory streaming combines both event workflow and Complex Event Processing (CEP) capabilities fully integrated in one product.

Processing of market feeds, electronic trading by many financial companies on Wall Street, security and fraud detection, real-time sales lead management—all these applications produce large amounts of data at very fast rates and require appropriate infrastructure capable of processing data in real-time without blockages.

One of the most common use cases for stream processing is the ability to control and properly pipeline distributed events workflow. As events are coming into the system at high rates, the processing of events is split into multiple stages and each stage has to be properly routed within a cluster for processing.

One of the key features of many CEP systems is the ability to control the scope of operations on streamed data. As streaming data never ends, an application must be able to provide a size limit or a time boundary on how far back each request or each query should go.

DATA FABRIC FEATURE: Hadoop Acceleration

With its In-Memory Data Fabric, GridGain offers Hadoop acceleration as well as a standalone In-Memory Accelerator for Hadoop built on top of the In-Memory Data Fabric, which expand the benefits of IMC to the Hadoop world by enabling enterprises to achieve unmatched performance and scale with their existing MapReduce and HIVE applications. All this is possible without requiring any code change to the native MapReduce, HDFS and YARN environment. This result is especially attractive for SaaS providers running analytics in a Hadoop distribution, a major milestone and turning point for Hadoop in the past year.

Prior to this offering, running IMC in an existing Hadoop environment required code changes to the application, reducing organization’s ability to quickly derive the full performance benefits of an in-memory architecture. The In-Memory Accelerator for Hadoop allows for true plug and

If you prefer, the complete insideAI News Guide to Hyperscaling Your SaaS Infrastructure is available for download in PDF from the insideAI News White Paper Library, courtesy of GridGain.