A HISTORIAN FOR DATA SCIENCE

ARE YOU HAVING ISSUES IN YOUR DATA INGESTION PROCESSES?

Ingestion

Having issues when ingesting large volumes of data? Does it take too long? 

Integration

Difficult software and tools integration?

Volume

Slow access to databases? 

Storage

Too little storage and processing capabilities? 

Cost

High cost and misuse of resources?

Data granularity

Not enough granularity/detail in your time series?

In short… are you unable to unify your workflow?

Ingestion

Having issues when ingesting large volumes of data? Does it take too long?

Integration

Difficult integration of software and tools?

Data volume

Slow access to databases?

Data capacity

Low storage and processing capabilities?

In short… are you unable to unify your workflow?

High costs

High cost and misuse of resources?

Data granularity

Not enough granularity/detail in your time series?

WHAT´S 

A System that allows to reliably store all those messages that a company can generate, without restrictions

INNOVATION PROPOSAL

INNOVATION PROPOSAL

YOU CAN DO THINGS DIFFERENTLY

Goodbye expensive Data Lake Solutions!

+STORE

Shapelets REC integrates natively within Shapelets Store, creating a cost-effective solution for both data science and process engineers to construct virtual data lakes on demand, where data can be use in context with other enterprise data sources.

COST-EFFECTIVE SOLUTIONS

Unlimited tags

Real-Time

Indexes data to achieve largest read throughputs

Long-term storage

Events, alarms, and metrics ideal for compliance, audit, crisis management and data science tasks

Ultra Ingestion

More than 100 million documents per second

Connectivity

Through industry standard protocols (ZeroMQ, MQTT, HTTPS, InfluxDB Line Protocol)

Compatibility with other systems

No more data aggregations

Extract the maximum value from data by keeping its original granularity

Native Python API

LICENSE

FLAT FEE YEARLY SUBSCRIPTION

   NO RESTRICTION

UP TO

90%

 OPEX savings

The fastest on the market

SOLUTION

TIME FOR
1M WRITES

~0.1 sec

~1.8 sec

~10.9 sec

~12.6 sec

~23.3 sec

~40 sec

TIME FOR
10M WRITES

~1 sec

~24.3 sec

~99.9 sec

~145 sec

NA

NA

SOLUTION

DATA MODEL

Tag-value

Relational

Tag-value

Relational

Hierarchical

Tag-value

SQL SUPPORT

Extensive

Extensive

Limited

Extensive

No

Limited

DISTRIBUTED COMPUTING

No
(Single machine, can be scaled horizontally)

No
(Single machine, can be scaled horizontally)

Yes
(Clustering, Sharding, High Availability)

Yes
(Automatic partitioning, Replication)

No
(Single machine, can be scaled horizontally)

Yes
(Clustering, Sharding)

TIME FOR
1M WRITES

~0.1 sec

~1.8 sec

~10.9 sec

~12.6 sec

~23.3 sec

~40 sec

TIME FOR
10M WRITES

~1 sec

~24.3 sec

~99.9 sec

~145 sec

NA

NA

FEATURES

Built-in HA, Data compression, Tiered Storage

 ACID Transactions, Built-in HA, Low Latency

 Continuous Queries, Retention Policies, Downsampling

Hypertables, Continuous Aggregates, Data Compression

Built-in Dashboarding, Graphing, Alerting

Built-in Aggregation, Data Rollups, Tiered Storage

  SETUP

REC server process installation, in cloud or on premise

More than 100 million messages per second

Select your storage configuration

(RAM only, RAM + local storage or RAM + local storage + cloud storage)

Start logging event data coming from

ZeroMQ, MQTT, HTTPS, InfluxDB Line Protocol, etc.-

  SETUP

1 REC server process installation, in cloud or on premise

More than 100 million messages per second using a simple server

2 Select your storage configuration

(RAM only, RAM + local storage or RAM + local storage + cloud storage)

3 Start logging event data coming from

ZeroMQ, MQTT, HTTPS, InfluxDB Line Protocol, etc

CONTACT US

Do you want to be the first to test it for Free?

Let us know today!

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