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DBMS > Databend vs. Elasticsearch vs. Google Cloud Datastore vs. TimescaleDB

System Properties Comparison Databend vs. Elasticsearch vs. Google Cloud Datastore vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Datastore  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 complexityA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSSearch engineDocument storeTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score4.47
Rank#76  Overall
#12  Document stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.elastic.co/­elasticsearchcloud.google.com/­datastorewww.timescale.com
Technical documentationdocs.databend.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­datastore/­docsdocs.timescale.com
DeveloperDatabend LabsElasticGoogleTimescale
Initial release2021201020082017
Current release1.0.59, April 20238.6, January 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC
Server operating systemshosted
Linux
macOS
All OS with a Java VMhostedLinux
OS X
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details herenumerics, 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.nononoyes
Secondary indexesnoyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (GQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyesusing Google App Engineuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infoby using the 'percolation' featureCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication using PaxosSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate 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.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DatabendElasticsearchGoogle Cloud DatastoreTimescaleDB
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