Today, cloud adoption has become mainstream as most businesses
have begun to invest heavily in consolidating and moving their data to the
cloud. However, when it comes to BI and data analytics, they face limitations
due to scale, costs or memory thresholds. Organizations face challenges in
analyzing all their data using existing BI tools and cloud architecture to meet
the performance SLAs or to justify the costs associated with analyzing
billion-scale datasets.
On the other hand, meeting the end user's expectations to
explore all their available data and deep-dive into the required metrics to get
answers isn't a piece of cake either. No matter how efficient the optimization
techniques deployed are, analysts still have to go through the hassle of sluggish
dashboards when data volume crosses a threshold or when complex queries are
fired. As a result, data analytics is delayed, decision-making suffers and the
end users do not get the insights they need in time.
This is why businesses need an analytics acceleration platform
that eliminates latency and delivers sub-second responses and can help them
analyze as much data on the cloud as required, irrespective of data size or
query complexity. Let's compare 5 leading acceleration platforms of 2023:
Snowflake
Snowflake is a cloud-agnostic data warehouse with a
comprehensive SaaS architecture and a fast and easy-to-use framework.
Organizations can use Snowflake to analyze data from multiple structured and
unstructured sources. Its multi-cluster design separates storage from
processing power enabling organizations to scale CPU resources based on user
activities.
With Snowflake, organizations can concurrently allocate
resources to the same database for loading and querying data without impacting
the data warehouse performance. Snowflake's pricing is based on a pay-per-use
model compared to other data warehousing solutions.
Kyvos
Kyvos is a modern, cloud-native analytics acceleration platform
that enables sub-second querying on massive datasets. Its ML-based smart
aggregation technology modernizes analytics and accelerates time to insights,
eliminating in-memory limitations. Kyvos' distributed querying framework along
with smart aggregates empowers organizations to instantly analyze data at any scale,
up to billions of records, irrespective of the analytics tool or underlying
cloud platform.
The platform's universal semantic layer democratizes data
across the enterprise through self-serve analytics. It acts as a modern layer
of business abstraction or, you can say, a central governance gateway
across the enterprise to prevent the data from unauthorized access.
Using Kyvos, enterprises can perform multidimensional analytics,
optimize cloud compute . It enables organizations to build a more agile
analytics platform for smarter and faster decision-making. Leveraging
ML-powered smart aggregates, users can drill down, roll up, slice and dice data
for granular insights and analyze any amount of historical and live data.
Starburst
Starburst is
a fully managed data lake analytics engine designed for distributed data
residing in a data warehouse, data lake, or data mesh. Starbursts allows
organizations to run interactive and ETL workloads using a single query engine,
significantly reducing data movement delays & costs. No matter where your
data lives, Starburst helps query data across any database, making it available
for data-driven decision-making.
Starburst can help organizations manage their big data costs by
providing true separation between storage and computing. It enables them to use
the compute resources necessary to meet the requirements. Starburst can connect
to all the data sources and BI tools to execute interactive analytical
queries.
Dremio
Dremio is an open data lakehouse platform that empowers data
engineers and analysts to quickly get started with self-service SQL analytics.
The solution enables data consumers to run BI workloads directly on the data
lake eliminating the need to move data into data warehouses or create
aggregation tables, or BI extracts.
Dremio's open architecture and intuitive interface allow data
access using any BI tool while ensuring flexibility and strict access control
for data consumers. The cloud and on-premises offerings of Dremio deliver cost
efficiencies and performance benefits across multiple clouds.
AtScale
Atscales's
universal semantic layer platform simplifies, accelerates, and enables analysts
to perform data analytics using popular BI tools. Itoffers a single, secured,
and governed workspace for distributed data.
With AtScale,
businesses are empowered to implement self-service BI and create one compliant
view of business metrics and definitions, controlling the complexity and costs of
analytics.
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