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DBMS > Apache IoTDB vs. Datastax Enterprise vs. EJDB vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Datastax Enterprise vs. EJDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonEJDB  Xexclude from comparisonSpark SQL  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 FlinkDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSWide column storeDocument storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.93
Rank#56  Overall
#4  Wide column stores
Score0.31
Rank#296  Overall
#44  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.datastax.com/­products/­datastax-enterprisegithub.com/­Softmotions/­ejdbspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datastax.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationDataStaxSoftmotionsApache Software Foundation
Initial release2018201120122014
Current release1.1.0, April 20236.8, April 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPLv2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCScala
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
server-lessLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, bool, date, object_idyes
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 indexesyesyesnono
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statements (CQL); Spark SQLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
in-process shared libraryJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infono "single point of failure"noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter aware, advanced replication for edge computingnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Foreign keys infoReferential integritynonono infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyes
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.yesyesno
User concepts infoAccess controlyesAccess rights for users can be defined per objectnono
More information provided by the system vendor
Apache IoTDBDatastax EnterpriseEJDBSpark SQL
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Apache IoTDBDatastax EnterpriseEJDBSpark SQL
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