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DBMS > EJDB vs. Google Cloud Datastore vs. Prometheus vs. TimescaleDB vs. TinkerGraph

System Properties Comparison EJDB vs. Google Cloud Datastore vs. Prometheus vs. TimescaleDB vs. TinkerGraph

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPrometheus  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-source Time Series DBMS and monitoring systemA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeDocument storeTime Series DBMSTime Series DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­datastoreprometheus.iowww.timescale.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsprometheus.io/­docsdocs.timescale.com
DeveloperSoftmotionsGoogleTimescale
Initial release20122008201520172009
Current release2.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGoCJava
Server operating systemsserver-lesshostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, details hereNumeric data onlynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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 infoImport of XML data possibleyesno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)noyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
TinkerPop 3
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Groovy
Java
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
TriggersnoCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosyes infoby FederationSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.noneImmediate Consistencynone
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsnoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardno

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More resources
EJDBGoogle Cloud DatastorePrometheusTimescaleDBTinkerGraph
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