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DBMS > Google Cloud Firestore vs. LevelDB vs. Manticore Search vs. Splice Machine

System Properties Comparison Google Cloud Firestore vs. LevelDB vs. Manticore Search vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonManticore Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCloud 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 valuesMulti-storage database for search, including full-text search.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value storeSearch engineRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.22
Rank#312  Overall
#21  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitefirebase.google.com/­products/­firestoregithub.com/­google/­leveldbmanticoresearch.comsplicemachine.com
Technical documentationfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdmanual.manticoresearch.comsplicemachine.com/­how-it-works
DeveloperGoogleGoogleManticore SoftwareSplice Machine
Initial release2017201120172014
Current release1.23, February 20216.0, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoGPL version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedIllumos
Linux
OS X
Windows
FreeBSD
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesnoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, 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.nonoCan index from XML
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query languageyes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsnouser defined functionsyes infoJava
Triggersyes, with Cloud Functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneSynchronous replication based on Galera libraryMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud FirestoreLevelDBManticore SearchSplice Machine
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