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DBMS > EsgynDB vs. Google Cloud Firestore vs. LevelDB vs. RRDtool vs. Splice Machine

System Properties Comparison EsgynDB vs. Google Cloud Firestore vs. LevelDB vs. RRDtool vs. Splice Machine

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonRRDtool  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud 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 valuesIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeKey-value storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.esgyn.cnfirebase.google.com/­products/­firestoregithub.com/­google/­leveldboss.oetiker.ch/­rrdtoolsplicemachine.com
Technical documentationfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdoss.oetiker.ch/­rrdtool/­docsplicemachine.com/­how-it-works
DeveloperEsgynGoogleGoogleTobias OetikerSplice Machine
Initial release20152017201119992014
Current release1.23, February 20211.8.0, 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen Source infoGPL V2 and FLOSSOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++C infoImplementations in Java (e.g. RRD4J) and C# availableJava
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
HP-UX
Linux
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoNumeric data onlyyes
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 infoExporting into and restoring from XML files possible
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesnononoyes
APIs and other access methodsADO.NET
JDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
in-process shared library
Pipes
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyes, Firebase Rules & Cloud Functionsnonoyes infoJava
Triggersnoyes, with Cloud Functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemonyes, 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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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
EsgynDBGoogle Cloud FirestoreLevelDBRRDtoolSplice Machine
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