Are You Ready for Machine-Scale Analytics?—
Human-scale
Data Value
$24B
Machine-scale
Data Value
$480B
Why Molecula’s Feature Store is the Future of Data Access—
Enterprises spend a lot of money preparing, aggregating and making numerous copies of their data to get it ready for analytics, machine learning and AI. The effort required to enable these projects far exceeds the value created. Molecula brings an entirely new paradigm for continuous, real-time data analysis and AI through its centralized feature store that eliminates the need to copy, move or pre aggregate data, maintains up-to-the-second updates, millisecond analytics performance, and provides a secure data format for data sharing.
Molecula Enterprise Feature Store—
Molecula provides centralized access to all your big data by reducing the dimensionality of the original source data , into a highly-optimized format that is natively predisposed for real-time machine-scale analytics and AI.
Feature Store
Molecula’s feature store is an overlay to conventional big data systems that centralizes an organization's most important entities and their attributes across various source systems, while maintaining up-to-the-second updates.
Extension Framework (SDK/API)
The extension framework provides an interface for external tools, libraries, models, and arbitrary code to be developed and applied to Molecula to extend functionality.
Control Plane
The control plane allows users to operate Molecula in hybrid environments to take advantage of both their on-premises, cloud, and edge infrastructures according to their workloads and needs.
Data Taps
Data Taps are used to ‘tap’ or ingest from source systems to continuously extract and update features and route them into Molecula. Easily query, select and extract features from Molecula and power your applications, preferred data science tools and machine learning pipelines.
Feature Store
Molecula’s feature store is an overlay to conventional big data systems that centralizes an organization's most important entities and their attributes across various source systems, while maintaining up-to-the-second updates.
Extension Framework (SDK/API)
The extension framework provides an interface for external tools, libraries, models, and arbitrary code to be developed and applied to Molecula to extend functionality.
Control Plane
The control plane allows users to operate Molecula in hybrid environments to take advantage of both their on-premises, cloud, and edge infrastructures according to their workloads and needs.
Data Taps
Data Taps are used to ‘tap’ or ingest from source systems to continuously extract and update features and route them into Molecula. Easily query, select and extract features from Molecula and power your applications, preferred data science tools and machine learning pipelines.
Data Taps Available Today—
In addition to a REST API, client libraries, and SQL support, Molecula has an extension framework to support plugins for most upstream and downstream systems, including ingest, data consumption, and security.
These taps are designed to connect to data sources ranging from databases (sql or nosql), to data pipelines and file systems in order to ingest data into Molecula.
Kafka
Ingest data from a Kafka topic into Molecula
Kafka Connect
Ingest data via Kafka Connect into Molecula
MySQL
Ingest data from MySQL database into Molecula
SQL
Ingest data from SQL Server database into Molecula
Snowflake
Ingest data from Snowflake data warehouse into Molecula
Cassandra
Ingest data from Cassandra database into Molecula
Teradata
Ingest data from Teradata data warehouse into Molecula
Spark
Ingest Spark data streams into Molecula
Parquet
Ingest Parquet files into Molecula
S3
Ingest files from your S3 instances into Molecula
Big Query
Ingest data from your Big Query data warehouse into Molecula
Use Monitoring Taps to connect Molecula to your logging or monitoring platform of choice.
Prometheus
Monitor your VDSs with Prometheus
Splunk
Monitor your VDSs with Splunk
Jaeger
Monitor your VDSs with Jaeger
StatsD
Collect metrics about your VDSs with StatsD
OpenTracing
Monitor your VDSs with OpenTracing
Datadog
Monitor your VDSs with Datadog
Consumption taps extend our API and Client Libraries to connect to systems that will use data in Molecula to visualize data, analyze it and ask questions of your data.
Tableau
Query your Molecula data using Tableau
Microsoft Power BI
Visualize your data with Microsoft Power BI
Jupyter Notebook
Query your Molecula data from your Jupyter Notebook
Pandas
Create Pandas data frames from Molecula VDSs
Snowflake
Query your Molecula data using Snowflake
RStudio
Query your Molecula data using RStudio
RAPIDS
Query your Molecula data using RAPIDS
JDBC Driver
Query your Molecula data with JDBC Driver
Molecula in action—
Molecula is an enterprise feature store that simplifies, accelerates, and controls big data access to power machine-scale analytics and AI. Continuously extracting features, reducing the dimensionality of data at the source and routing real-time feature changes into a central store enables millisecond queries, computation and feature re-use across formats and locations without copying or moving raw data.
Data in real time delivers real advantages—
With Molecula, your entire team will see significant, job-changing enhancements to the way they’re able to perform their jobs.
Data Engineers
Simplify analytics, AI and machine learning infrastructure with one centralized feature store for all projects.
Advantages—
- 100% data access via centralized features up to PB scale
- Most performant, secure unified access
- Any data format, location and no pre-aggregation
- No data copies or movement
Data Scientists and Application Developers
Accelerate time from data to business outcome by enabling real-time, predictive and personalized use cases.
Advantages—
- Instant, continuous, deeper insights across any data sets
- Millisecond performance
- Eliminate the need to pre-join siloed datasets
- Lower time to value with fast queries and no data delivery cycles
IT and Security Team
Control data access, compliance risk and costs with a more secure data format for sharing and reduced data footprint.
Advantages—
- Securely share features without copying data
- Meet compliance and governance requirements
- Reduce infrastructure costs by orders of magnitude
Product Capabilities—
Extracts Feature from Data
‘AI Ready’ feature store that continuously extracts and updates features in real-time
Offers Single Point of Access
Centralized, ultra low latency access to all of your data
Supports ML Workloads
High concurrency queries for machine-scale analytics and ML
Eliminates Pre-Processing
Performant Joins at query time, with no pre-aggregation or pre-processing
Reduces Footprint
Lossless reduction in data footprint, up to 85%, without copying or moving data
Easily-Adoptable Overlay Implementation
Extension framework enabling seamless integration into existing environments
Enables Time-Oriented Filtering
Track and filter time at a feature level
Delivers Secure, Cell-Level Control
Granular access control of feature sharing down to the cell level
Related Resources—
Molecula’s novel approach to data access breaks through the latency floor created by the zoo of legacy data processing technologies, eliminating the need to pre-aggregate, federate, copy, cache or move source data.
View ResourceMolecula is a Cloud Data Access Platform that simplifies, accelerates, and controls data access for advanced analytics, Machine Learning, and edge/IoT.
View ResourceIn this paper we introduce a novel approach to data virtualization which is making strides to clear the log jam that has increasingly plagued data beneficiaries for years.
View ResourceCalculate Your TCO with Molecula
Molecula's novel approach to data access is game changing for your machine-scale analytics and AI. By simplifying real-time analytics and AI infrastructure Molecula can reduce footprint by 60-90% and save you time, resources, and headaches. Come see for yourself.