DBMS > Apache IoTDB vs. eXtremeDB vs. H2
System Properties Comparison Apache IoTDB vs. eXtremeDB vs. H2
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|Editorial information provided by DB-Engines
|Apache IoTDB Xexclude from comparison
|eXtremeDB Xexclude from comparison
|H2 Xexclude from comparison
|An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink
|Natively in-memory DBMS with options for persistency, high-availability and clustering
|Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
|Primary database model
|Time Series DBMS
Time Series DBMS
|Secondary database models
|Apache Software Foundation
|1.1.0, April 2023
|2.2.220, July 2023
|License Commercial or Open Source
|Open Source Apache Version 2.0
|Open Source dual-licence (Mozilla public license, Eclipse public license)
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
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|C and C++
|Server operating systems
|All OS with a Java VM (>= 1.8)
|All OS with a Java VM
|Typing predefined data types such as float or date
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.
|no support of XML interfaces available
|SQL Support of SQL
|SQL-like query language
|yes with the option: eXtremeSQL
|APIs and other access methods
|.NET Client API
RESTful HTTP API
|Supported programming languages
|Server-side scripts Stored procedures
|Java Stored Procedures and User-Defined Functions
|yes by defining events
|Partitioning methods Methods for storing different data on different nodes
|horizontal partitioning (by time range) + vertical partitioning (by deviceId)
|horizontal partitioning / sharding
|Replication methods Methods for redundantly storing data on multiple nodes
|selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas
|Active Replication Fabric™ for IoT
Multi-source replication by means of eXtremeDB Cluster option
Source-replica replication by means of eXtremeDB High Availability option
|With clustering: 2 database servers on different computers operate on identical copies of a database
|MapReduce Offers an API for user-defined Map/Reduce methods
|Integration with Hadoop and Spark
|Consistency concepts Methods to ensure consistency in a distributed system
Strong Consistency with Raft
|Foreign keys Referential integrity
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|Concurrency Support for concurrent manipulation of data
|yes Optimistic (MVCC) and pessimistic (locking) strategies available
|yes, multi-version concurrency control (MVCC)
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|fine grained access rights according to SQL-standard
|More information provided by the system vendor
|eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
|eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
|Typical application scenarios
|IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
|Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
|With hundreds of customers and over 30 million devices/applications using the product...
|Licensing and pricing models
|For server use cases, there is a simple per-server license irrespective of the number...
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