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DBMS > Databend vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. VictoriaMetrics

System Properties Comparison Databend vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonVictoriaMetrics  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 complexityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldvictoriametrics.com
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperDatabend LabsGoogleHEAVY.AI, Inc.GoogleVictoriaMetrics
Initial release20212008201620142018
Current release1.0.59, April 20235.10, January 20222.1.12, February 2017v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
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 languageRustC++ and CUDAJavaScriptGo
Server operating systemshosted
Linux
macOS
hostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like query language infovia JavaScript builder patternno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
JavaScript
Server-side scripts infoStored proceduresnousing Google App Enginenonono
TriggersnoCallbacks using the Google Apps EnginenoUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosMulti-source replicationnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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.Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBno
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-standardno

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More resources
DatabendGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldVictoriaMetrics
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