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

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

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPrometheus  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityEmbeddable 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 PostgreSQL
Primary database modelRelational DBMSDocument storeDocument storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
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
Websitegithub.com/­datafuselabs/­databend
www.databend.com
github.com/­Softmotions/­ejdbcloud.google.com/­datastoreprometheus.iowww.timescale.com
Technical documentationdocs.databend.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsprometheus.io/­docsdocs.timescale.com
DeveloperDatabend LabsSoftmotionsGoogleTimescale
Initial release20212012200820152017
Current release1.0.59, April 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustCGoC
Server operating systemshosted
Linux
macOS
server-lesshostedLinux
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, details hereNumeric data onlynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonono infoImport of XML data possibleyes
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)noyes infofull PostgreSQL SQL syntax
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
in-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
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Actionscript
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
Server-side scripts infoStored proceduresnonousing 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 shell
TriggersnonoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication using Paxosyes infoby FederationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
DatabendEJDBGoogle Cloud DatastorePrometheusTimescaleDB
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