DBMS > Apache IoTDB vs. ArangoDB vs. H2
System Properties Comparison Apache IoTDB vs. ArangoDB vs. H2
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|Editorial information provided by DB-Engines
|Apache IoTDB Xexclude from comparison
|ArangoDB 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
|Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.
|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
|Secondary database models
|Social network pages
|Apache Software Foundation
|1.1.0, April 2023
|3.11.5, November 2023
|2.2.220, July 2023
|License Commercial or Open Source
|Open Source Apache Version 2.0
|Open Source Apache Version 2; Commercial license (Enterprise) available
|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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|ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
|Server operating systems
|All OS with a Java VM (>= 1.8)
|All OS with a Java VM
|schema-free automatically recognizes schema within a collection
|Typing predefined data types such as float or date
|yes string, double, boolean, list, hash
|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.
|SQL Support of SQL
|SQL-like query language
|APIs and other access methods
Graph API (Gremlin)
GraphQL query language
Java & SpringData
JSON style queries
|Supported programming languages
|Server-side scripts Stored procedures
|Java Stored Procedures and User-Defined Functions
|Partitioning methods Methods for storing different data on different nodes
|horizontal partitioning (by time range) + vertical partitioning (by deviceId)
|Sharding since version 2.0
|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
|Source-replica replication with configurable replication factor
|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
|Eventual Consistency configurable per collection or per write
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
|Foreign keys Referential integrity
|yes relationships in graphs
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|Concurrency Support for concurrent manipulation of data
|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
|Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
|Consolidation: As a native multi-model database, can be used as a full blown document...
|Typical application scenarios
|Native multi-model in ArangoDB is being used for a broad range of projects across...
|Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
|ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
|Licensing and pricing models
|Very permissive Apache 2 License for Community Edition & commercial licenses are...
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