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DBMS > Apache Drill vs. Apache IoTDB vs. Ignite vs. Microsoft Azure Table Storage

System Properties Comparison Apache Drill vs. Apache IoTDB vs. Ignite vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache IoTDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitedrill.apache.orgiotdb.apache.orgignite.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdrill.apache.org/­docsiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlapacheignite.readme.io/­docs
DeveloperApache Software FoundationApache Software FoundationApache Software FoundationMicrosoft
Initial release2012201820152012
Current release1.20.3, January 20231.1.0, April 2023Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .Net
Server operating systemsLinux
OS X
Windows
All OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
hosted
Data schemeschema-freeyesyesschema-free
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.nonoyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languageANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesC++C
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesyes (compute grid and cache interceptors can be used instead)no
Triggersnoyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesyesno
User concepts infoAccess controlDepending on the underlying data sourceyesSecurity Hooks for custom implementationsAccess rights based on private key authentication or shared access signatures

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More resources
Apache DrillApache IoTDBIgniteMicrosoft Azure Table Storage
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