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DBMS > Apache IoTDB vs. IBM Db2 Event Store vs. RavenDB vs. Sphinx

System Properties Comparison Apache IoTDB vs. IBM Db2 Event Store vs. RavenDB vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  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 Event Store optimized for Internet of Things use casesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSEvent Store
Time Series DBMS
Document storeSearch engine
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score2.68
Rank#102  Overall
#19  Document stores
Score5.97
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.ibm.com/­products/­db2-event-storeravendb.netsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storeravendb.net/­docssphinxsearch.com/­docs
DeveloperApache Software FoundationIBMHibernating RhinosSphinx Technologies Inc.
Initial release2018201720102001
Current release1.1.0, April 20232.05.4, July 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C#C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infoLinux, macOS, Windows for the developer additionLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.nono
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyes infothrough the embedded Spark runtimeSQL-like query language (RQL)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyesyesno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive-active shard replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAuthorization levels configured per client per databaseno

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Apache IoTDBIBM Db2 Event StoreRavenDBSphinx
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