Apache Druid vs. AVEVA Historian

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Druid
Score 9.0 out of 10
N/A
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture.N/A
AVEVA Historian
Score 9.2 out of 10
N/A
AVEVA Historian, formerly from Wonderware, is a time-series optimized data store, allowing the user to capture and store high-fidelity industrial big data, to unlock trapped potential for operational improvements.N/A
Pricing
Apache DruidAVEVA Historian
Editions & Modules
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Offerings
Pricing Offerings
DruidAVEVA Historian
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache DruidAVEVA Historian
Top Pros

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Top Cons

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Best Alternatives
Apache DruidAVEVA Historian
Small Businesses
InfluxDB
InfluxDB
Score 8.5 out of 10
InfluxDB
InfluxDB
Score 8.5 out of 10
Medium-sized Companies

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Enterprises

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User Ratings
Apache DruidAVEVA Historian
Likelihood to Recommend
9.0
(1 ratings)
8.0
(1 ratings)
User Testimonials
Apache DruidAVEVA Historian
Likelihood to Recommend
Apache
It is extremely well suited to rapid ingest of data from large data sources, due to the fact that you can restrict what is ingested by column/field, so that you only pull in the data you actually want or need.
As stated earlier, the open source version could use better cluster management tools, and troubleshooting tools for failing jobs/tasks.
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AVEVA
Paired with Citect SCADA or System Platform, this is an excellent process historian. It also works well collecting OPC data. For basic data storage, retrieval, and analysis, this is well suited. This is not well suited for very large deployments. Multiple instances would need to be used to scale up, and the data fed into a second-tier/enterprise historian for corporate user consumption.
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Pros
Apache
  • Rapid ingest
  • Limiting ingest to only the relevant fields/columns
  • Easy ingest spec creation
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AVEVA
  • Data storage--multiple data sources stream data in real time; it is stored without issue
  • Data retrieval--small to moderate queries and trends are generally fast and efficient
  • Cost effectiveness--it is one of the cheaper (non-enterprise) historian offers and therefore is good value for money (with a reduced feature set)
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Cons
Apache
  • Security configuration is problematic
  • Cluster management could have more features
  • Troubleshooting incomplete tasks/jobs is a chore
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AVEVA
  • Query performance--for very long-term/large queries; the latest version which we are yet to commission has some improvements in this area
  • User interface--the trend, query, and Excel add-ins are basic and could do with a refresh; web-based clients are a paid add-on and less full featured, so not a true replacement
  • Connectivity--Wonderware System Platform driver packs are required for additional data source types, where native connectors are not provided by other products
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Alternatives Considered
Apache
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AVEVA
AVEVA Historian, formerly Wonderware, was the best of the process tier historians in terms of reliability and functionality. It is still under development and not a "dead" product. It is also more cost effective than the more full-featured enterprise historians, such as PI, which our organization is not yet ready for. The feature set is at the right cost level, coupled with current support, were the key factors in the decision.
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Return on Investment
Apache
  • Integration with S3 storage has saved about 35% on our storage, over HDFS
  • The rapid ingest has saved user's time in the query aspects of their applications.
  • The ability to ingest from a variety of data sources has made overall user application queries much simpler
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AVEVA
  • Increased efficiency, reduction in labour for preparing reports--data is available to be queried and reported with less effort
  • Increased production efficiency--near real-time data availability and comparisons to historical data has been used to make faster and better operational decisions
  • Increased reliability--data has been used for maintenance optimization and planning purposes
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