MapD Core Database

The world's fastest in-memory, distributed GPU database powers the world's most immersive data exploration experience. Now open source.
The Database Designed for GPUs

MapD Core is an in-memory, column store, SQL relational database that was designed from the ground up to run on GPUs. The parallel processing power of GPU hardware enables the MapD Core database to query billions of rows in milliseconds using standard SQL.

Lightning Fast

The MapD Core database is orders of magnitude faster than even the fastest CPU solutions in third-party benchmark tests. Get insights quicker from your data with the parallel power of GPUs.

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Data source: Summary of the 1.1 Billion Taxi Rides Benchmarks at http://tech.marksblogg.com/benchmarks.html
Query 1 SELECT cab_type, count() FROM trips GROUP BY cab_type;
Query 2 SELECT passenger_count, avg(total_amount) FROM trips GROUP BY passenger_count;
Query 3 SELECT passenger_count, extract(year from pickup_datetime) AS pickup_year, count() FROM trips GROUP BY passenger_count, pickup_year;
Query 4 SELECT passenger_count, extract(year from pickup_datetime) AS pickup_year, cast(trip_distance as int) AS distance, count(*) AS the_count FROM trips GROUP BY passenger_count, pickup_year, distance ORDER BY pickup_year, the_count desc;
System configurations
MapD: 1 machine (16 cores, 512 GB RAM, 2 x 1TB SSD, 8 Nvidia Pascal Titan X GPUs)
Redshift: 6 machines (36 cores, 244 GB RAM, 16TB HDD, AWS ds2.8xlarge)
Presto: 50 machines (4 cores, 15 GB RAM, 100GB SSD, GCP n1-standard-4)
Spark: 11 machines (4 cores, 15 GB RAM, 2 X 40GB storage, AWS m3.xlarge)
Benefits of GPU Power
Freedom from Indexes
The parallel power of MapD Core database means that indexes are not required to achieve the best query performance. Queries are just effortlessly fast, no index creation or maintenance required.
No Need to Downsample
There is no need to downsample data to reduce load on the system. GPU-powered MapD Core has the performance to process billions of rows and terabytes of in-memory data even on a single node.
Intelligent Scale
A single MapD server using GPUs can deliver the same work as dozens, if not hundreds, of CPU-only servers. For many workloads a single server is all that is required, if more capacity is needed a cluster of servers can be used.
Speaks SQL Natively

MapD Core is a native SQL database. It runs SQL, the data language your organization already knows, but at speeds hundreds of times faster than CPU-based solutions.

MapD Core database can filter, group, aggregate and join billions of rows of data in milliseconds, allowing for interactive ad-hoc exploration of the massive datasets. And it fits easily into existing data ecosystems, with support for a wide range of connectivity options to databases and data sources including JDBC, ODBC, Apache Thrift, Kafka, and Sqoop. And ODBC and JDBC support also provides SQL connectivity to third party tools including Tableau, Birst, MicroStrategy, and Qlik, again using standard SQL.

Enterprise Scale & Durability
Distributed Scale-out
The MapD Core database includes native distributed scale-out capability which allows database size and query performance to scale as servers are added. Thanks to the parallel processing power of GPUs, MapD Core customers can query and visualize larger datasets with much smaller cluster sizes than CPU-only solutions.
High Availability
The MapD Core database includes high availability functionality that gives customers enterprise-grade durability and redundancy by replicating data across multiple servers. Inserts are distributed seamlessly across the cluster while read queries are load balanced between servers for additional throughput.
MapD Core Deep Technology

Fast Compiled SQL

MapD Core database SQL queries are compiled with a just-in-time (JIT) LLVM based compiler, and run as NVIDIA GPU and x64 CPU machine code. In-memory CPU-based databases often use slow interpreters or source-to-source compilers. MapD compiled queries deliver performance up to orders of magnitude faster.

Advanced Memory Management

MapD Core transparently manages the super-fast VRAM of the GPUs along with the main systems memory to achieve peak performance. Data is intelligently moved between main memory and GPU VRAM as needed. The system can also leverage modern fast SSDs for persistent storage. This advanced memory management enables the MapD Core database to deliver exceptional performance across different hardware configurations and database sizes.

Hybrid execution

MapD Core fully exploits the performance of both GPUs and CPUs. The database can simultaneously execute compiled queries across multiple GPUs and CPUs. And it uses the same infrastructure to parallelize computation across all CPUs as it does all GPUs—delivering leading performance even on CPU only systems.

MapD Core Rendering Engine

The MapD Core database includes a powerful rendering engine which renders the results of SQL queries as PNG compressed image files, all in-situ on the server GPU. This gives users the ability to visualize billions of records in pixel-perfect visualizations without the need to send multi-gigabyte result sets from server to client.

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