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DBMS > Apache IoTDB vs. Google Cloud Firestore vs. LevelDB vs. Pinecone vs. Splice Machine

System Properties Comparison Apache IoTDB vs. Google Cloud Firestore vs. LevelDB vs. Pinecone vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  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 FlinkCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSDocument storeKey-value storeVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­firestoregithub.com/­google/­leveldbwww.pinecone.iosplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperApache Software FoundationGoogleGooglePinecone Systems, IncSplice Machine
Initial release20182017201120192014
Current release1.1.0, April 20231.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)hostedIllumos
Linux
OS X
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoString, Number, Booleanyes
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
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languagenononoyes
APIs and other access methodsJDBC
Native API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
PythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes, Firebase Rules & Cloud Functionsnoyes infoJava
Triggersyesyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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 replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkUsing Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.noAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBGoogle Cloud FirestoreLevelDBPineconeSplice Machine
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