Works natural with iterative development cycles
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THIS IS YOU ?an agile development teamlooking for more flexible ways to clean, store, reshape and retrieve massive (sensor) data for your applicationexperience performance bottleneckswith your current data storage architecture or need advice on minimising latencyinterested in levelling logicfrom the application to the data layer such as application subscriptions to real time data changes or document validation using JSON schemaneed your existing BI analytics toolsto talk to MongoDBneed PII compliancyfor all your data at rest and in flightexploring non relational databases such as MongoDBfor horizontal scaling and need advise and supportMASSIVEQUERIES HAS THE KNOW HOW AND EXPERTISE TO HELP YOU OUT WITH SELF MANAGED DOCUMENT STORESsolving issues with PASSION and total DEDICATIONlicense # 895-280-785license # 492-746-001
SERVICE & SUPPORT
deployment & operations
diagnostics
debugging, f.e. slow queries, network socket exceptions, spikes in number of connections
performance tuning
optimizing storage engine and network parameters. f.e. intra-cluster compression
low-level benchmarking e.o.
security
securing data for PII compliance using encryption and redaction
connectivity
integrating SQL Business Intelligence tools
connecting to Hadoop and Spark tools
development
support with schema design and transition from SQL to noSQL
BENEFITS
Dynamic Data Structure
Documents can include arrays
Related data may be stored in a single document without the need of normalization, avoiding inefficient joins and therefore resulting in much faster response times
Horizontal Scalability
You can easily scale up or down your system by adding or removing shards from your cluster
High Availability
Through the implementation of replication sets with each shard, you get automatic failover
Optimised distribution
You can distribute your cluster nodes not only geographically, but also tiered, according to application/client affinity or any other distribution which is optimal for your application.
Built for massive data retrieval and analytics
MongoDB provides an expressive query language and aggregation framework.
It has built-in tools for analytics, such as facets.
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