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DBMS > Apache IoTDB vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage

System Properties Comparison Apache IoTDB vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  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 FlinkDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelTime Series DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteiotdb.apache.orgdgraph.iowww.esgyn.cncloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldgraph.io/­docscloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationDgraph Labs, Inc.EsgynGoogleMicrosoft
Initial release20182016201520152012
Current release1.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linuxhostedhosted
Data schemeyesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query languagenoyesnono
APIs and other access methodsJDBC
Native API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoJava Stored Proceduresnono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesShardingShardingSharding 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 replicasSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes 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 Sparknoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlyesno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signatures

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More resources
Apache IoTDBDgraphEsgynDBGoogle Cloud BigtableMicrosoft Azure Table Storage
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