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DBMS > AllegroGraph vs. Google Cloud Datastore vs. HarperDB vs. Heroic

System Properties Comparison AllegroGraph vs. Google Cloud Datastore vs. HarperDB vs. Heroic

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Websiteallegrograph.comcloud.google.com/­datastorewww.harperdb.iogithub.com/­spotify/­heroic
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlcloud.google.com/­datastore/­docsdocs.harperdb.io/­docsspotify.github.io/­heroic
DeveloperFranz Inc.GoogleHarperDBSpotify
Initial release2004200820172014
Current release8.0, December 20233.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsJava
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Data schemeyes infoRDF schemasschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyes infoJSON 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.no infobulk load of XML files possiblenonono
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)SQL-like data manipulation statementsno
APIs and other access methodsRESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispusing Google App EngineCustom Functions infosince release 3.1no
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infothe nodes on which a table resides can be definedyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles
More information provided by the system vendor
AllegroGraphGoogle Cloud DatastoreHarperDBHeroic
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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