Tervela's Big Data Movement Appliance provides real-time data access, disaster recovery, and global distribution for large data warehouses

1. Big Data Movement Appliance
Product Overview

2. Big Data Movement Appliance
Data Warehouses are under significant pressure to
expand capacity and make information available faster
Tervela provides a big data movement appliance for data warehouse
& analytics owners that:
• Turns active-standby disaster recovery into active-active
• Provides real-time data acquisition, distribution, processing, and
loading for warehouses
• Executes high-performance data ingress
• Automatically buffers data during peak load
• Preserves investment in existing technologies
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3. Data Warehousing With Tervela
On Demand Web Stack
(Java, .NET, PHP, Ruby) Tervela Appliances REPORTING
(physical or virtual)
File System vBDMA
(CIFS, NFS) BI Analytics
A D A P T E R S
NoSQL/NewSQL
BDMA
(Vertica, Hadoop)
Financial data
(Oracle, IBM)
ETL
Operational Data Store
(MySQL, Oracle, DB2) BDMA
ERP
(SAP, Oracle)
Middleware
(TIBCO, MQ, ActiveMQ)
vBDMA
Primary Data
Cloud-based CRM Warehouse
(Salesforce,
Oracle) Secondary Data
Warehouse
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4. With Our Solution…
1. Turn hot-cold data warehouses into hot-hot systems…
Effectively doubling capacity for incremental investment.
2. Provide real-time access to data and analytics…
Satisfying customer demand for faster and more comprehensive
access to data and decision support.
3. Distribute warehoused data across the globe…
Supporting global demand for information in real-time.
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5. Hot-Hot Backup & Disaster Recovery
Hot-Cold DR Hot-Hot DR
with Tervela
Apps Apps (can be virtualized)
Primary Data Center
DBs & File Systems BDMA Tervela
Data guaranteed
available in the
fabric, even if not
Restore yet archived to
required in remote servers
case of No restore
disaster required
Local Cloud
Secondary Cloud Data Backup All data centers
data center Backup Center Remote are active, utilized
Data
Center
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6. Distributed Operational Data Stores
• ODS systems operate
Kirkland ODS as regional big data
• Persisted data and
BDMA
interesting events are
New York identified and
ODS
Oakland ODS propagated onto the
fabric
BDMA
BDMA
Data • Tervela moves data to
Aggregated Baltimore ODS
Central BI Fabric the central BI system:
• High-performance
BDMA
• High reliability
• Buffered ingress
• Slow consumer
BDMA
management
Orlando ODS
• Relevant data or events
can be sent back out to
BDMA
regional systems 6

7. Sensor Networks
• Central grids
Health
synchronized across
Store Sensors Patient Data data fabric backbone
Information
• Sensors connect to data
fabric through virtual
vDBMA
vBDMA vBDMA appliances
• Data uploaded into the
Data Fabric fabric by sensors is
BDMA immediately available,
BDMA
even before persisted in
BDMA
grids
East
West • Data fabric buffers
Central
Central ingress for burst
Mid Grid
Grid management & slow
Central
consumers
Grid
• Connection Aggregation
and Footprint Reduction
reducing infrastructure
requirements
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