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DBMS > Apache IoTDB vs. Graphite vs. HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer

System Properties Comparison Apache IoTDB vs. Graphite vs. HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraphite  Xexclude from comparisonHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  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 logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA fast-speed and highly-scalable Graph DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platform
Primary database modelTime Series DBMSTime Series DBMSGraph DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score4.75
Rank#75  Overall
#5  Time Series DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websiteiotdb.apache.orggithub.com/­graphite-project/­graphite-webgithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgraphite.readthedocs.iohugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationChris DavisBaiduApache Software FoundationMicrosoft
Initial release20182006201820152019
Current release1.1.0, April 20230.9Apache Ignite 2.6cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPythonJavaC++, Java, .Net
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Linux
macOS
Unix
Linux
OS X
Solaris
Windows
hosted
Data schemeyesyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nononoyesyes
Secondary indexesyesnoyes infoalso supports composite index and range indexyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Native API
HTTP API
Sockets
Java API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaScript (Node.js)
Python
Groovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersyesnonoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding 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 replicasnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (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 methodsIntegration with Hadoop and Sparknovia hugegraph-sparkyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesnoUsers, roles and permissionsSecurity Hooks for custom implementationsAzure Active Directory Authentication

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More resources
Apache IoTDBGraphiteHugeGraphIgniteMicrosoft Azure Data Explorer
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