Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions. It supports aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets, High performance merging and joining of data sets, Time series-functionality, Hierarchical axis indexing and lot more. 

Pandas - Powerful Python Data Analysis Toolkit

EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries. Its features include Automatic partitioning, Columnar storage, Standard SQL support, Scales to petabytes, Timeseries and relational data, Fast range scans and lot more.
 
Use case: 
<ul>
 <li>
 Storage and analysis of streaming event, timeseries or relational data
 </li>
 <li>
 High volume event and sensor data logging
 </li>
 <li>
 Joining and correlating of timeseries data with relational tables
 </li>
 </ul>

 EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries. Its features include Automatic partitioning, Columnar storage, Standard SQL support, Scales to petabytes, Timeseries and relational data, Fast range scans and lot more.

EventQL - The database for large-scale event analytics

GridDB is an In-Memory NoSQL Database for highly scalable IoT applications . It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors. High Reliability It is equipped with a structure to spread out the replication of key value data among fellow nodes so that in the event of a node failure, automatic failover can be carried out in a matter of seconds by using the replication function of other nodes.
 
GridDB utilizes a “Memory first, Storage second” structure. “Hot” data is kept in-memory, allowing for much faster writes/reads on the most-used data.

 GridDB is an In-Memory NoSQL Database for highly scalable IoT applications . It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors. High Reliability It is equipped with a structure to spread out the replication of key value data among fellow nodes so that in the event of a node failure, automatic failover can be carried out in a matter of seconds by using the replication function of other nodes. 

Griddb - High performance, High scalability and High reliability database for big data

MarketStore is a database server optimized for financial timeseries data. You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, including tick-level for the all US equities or the exploding crypto currencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem.
 
The batteries are included so you can start pulling crypto price data from GDAX right after you install MarketStore. Then you can query DataFrame content over the network at as low latency as your local HDF5 files from disk, and appending new data to the end is two orders of magnitude faster than DataFrame would be. This is because the storage format is optimized for the type of data and use cases as well as for modern filesystem/hardware characteristics.

 MarketStore is a database server optimized for financial timeseries data. You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, including tick-level for the all US equities or the exploding crypto currencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem.

Marketstore - DataFrame Server for Financial Timeseries Data

Gnocchi is an open-source |time series| database. The problem that Gnocchi solves is the storage and indexing of |time series| data and resources at a large scale. This is useful in modern cloud platforms which are not only huge but also are dynamic and potentially multi-tenant. Gnocchi takes all of that into account. Gnocchi has been designed to handle large amounts of aggregates being stored while being performant, scalable and fault-tolerant. While doing this, the goal was to be sure to not build any hard dependency on any complex storage system.
 
Gnocchi takes a unique approach to time series storage: rather than storing raw data points, it aggregates them before storing them. This built-in feature is different from most other time series databases, which usually support this mechanism as an option and compute aggregation (average, minimum, etc.) at query time.

Gnocchi is an open-source |time series| database. The problem that Gnocchi solves is the storage and indexing of |time series| data and resources at a large scale. This is useful in modern cloud platforms which are not only huge but also are dynamic and potentially multi-tenant. Gnocchi takes all of that into account. Gnocchi has been designed to handle large amounts of aggregates being stored while being performant, scalable and fault-tolerant. While doing this, the goal was to be sure to not build any hard dependency on any complex storage system.

Gnocchi - Time series database

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Pandas - Powerful Python Data Analysis Toolkit

EventQL - The database for large-scale event analytics

Griddb - High performance, High scalability and High reliability database for big data

Marketstore - DataFrame Server for Financial Timeseries Data

Gnocchi - Time series database

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Pandas - Powerful Python Data Analysis Toolkit

EventQL - The database for large-scale event analytics

Griddb - High performance, High scalability and High reliability database for big data

Marketstore - DataFrame Server for Financial Timeseries Data

Gnocchi - Time series database

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