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DBMS > AgensGraph vs. Apache Doris vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield

System Properties Comparison AgensGraph vs. Apache Doris vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Doris  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAn MPP-based analytics DBMS embracing the MySQL protocolAutomatically 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 JavaScript
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#320  Overall
#29  Graph DBMS
#143  Relational DBMS
Score0.61
Rank#235  Overall
#110  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.22
Rank#306  Overall
#138  Relational DBMS
Websitebitnine.net/­agensgraphdoris.apache.org
github.com/­apache/­doris
cloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefield
Technical documentationbitnine.net/­documentationgithub.com/­apache/­doris/­wikicloud.google.com/­datastore/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperBitnine Global Inc.Apache Software Foundation, originally contributed from BaiduGoogleHEAVY.AI, Inc.Google
Initial release20162017200820162014
Current release2.1, December 20181.2.2, February 20235.10, January 20222.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen 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 languageCJavaC++ and CUDAJavaScript
Server operating systemsLinux
OS X
Windows
LinuxhostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemedepending on used data modelyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, 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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like query language (GQL)yesSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsCypher Query Language
JDBC
JDBC
MySQL client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Supported programming languagesC
Java
JavaScript
Python
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
JavaScript
Server-side scripts infoStored proceduresyesuser defined functionsusing Google App Enginenono
TriggersnonoCallbacks using the Google Apps EnginenoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioningShardingSharding infoRound robinnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication using PaxosMulti-source replicationnone
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 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 Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes infousing MemoryDB
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess 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
AgensGraphApache DorisGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Lovefield
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