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DBMS > Apache IoTDB vs. Hive vs. ScyllaDB vs. VelocityDB

System Properties Comparison Apache IoTDB vs. Hive vs. ScyllaDB vs. VelocityDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHive  Xexclude from comparisonScyllaDB  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flinkdata warehouse software for querying and managing large distributed datasets, built on HadoopCassandra and DynamoDB compatible wide column storeA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelTime Series DBMSRelational DBMSWide column storeGraph DBMS
Object oriented DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websiteiotdb.apache.orghive.apache.orgwww.scylladb.comvelocitydb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.scylladb.comvelocitydb.com/­UserGuide
DeveloperApache Software FoundationApache Software Foundation infoinitially developed by FacebookScyllaDBVelocityDB Inc
Initial release2018201220152011
Current release1.1.0, April 20233.1.3, April 2022ScyllaDB Open Source 5.4.1, January 20247.x
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoOpen Source (AGPL), commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C#
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxAny that supports .NET
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesyes infocluster global secondary indicesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL)no
APIs and other access methodsJDBC
Native API
JDBC
ODBC
Thrift
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
.Net
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
PHP
Python
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
.Net
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceyes, Luano
TriggersyesnonoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factorselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoin-memory tablesyes
User concepts infoAccess controlyesAccess rights for users, groups and rolesAccess rights for users can be defined per objectBased on Windows Authentication
More information provided by the system vendor
Apache IoTDBHiveScyllaDBVelocityDB
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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Apache IoTDBHiveScyllaDBVelocityDB
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