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DBMS > Apache IoTDB vs. EXASOL vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

System Properties Comparison Apache IoTDB vs. EXASOL vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 FlinkHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelTime Series DBMSRelational DBMSDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Wide column store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Websiteiotdb.apache.orgwww.exasol.comfirebase.google.com/­products/­realtime-databasewww.gigaspaces.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourcesfirebase.google.com/­docs/­databasedocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software FoundationExasolGoogle infoacquired by Google 2014Gigaspaces TechnologiesHypertable Inc.
Initial release20182000201220002009
Current release1.1.0, April 202315.5, September 20200.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
macOS
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLSQL-like query languageyesnoSQL-99 for query and DML statementsno
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
C++ API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
Java
JavaScript
Objective-C
.Net
C++
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functionslimited functionality with using 'rules'yesno
TriggersyesyesCallbacks are triggered when data changesyes, event driven architectureno
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 replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
selectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoHadoop integrationnoyes infoMap-Reduce pattern can be built with XAP task executorsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDno
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.yesyesyes
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesRole-based access controlno

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More resources
Apache IoTDBEXASOLFirebase Realtime DatabaseGigaSpacesHypertable
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