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DBMS > AllegroGraph vs. Apache Impala vs. Google Cloud Datastore vs. IBM Db2 Event Store

System Properties Comparison AllegroGraph vs. Apache Impala vs. Google Cloud Datastore vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use cases
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSDocument storeEvent Store
Time Series DBMS
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Websiteallegrograph.comimpala.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­db2-event-store
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperFranz Inc.Apache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleIBM
Initial release2004201320082017
Current release8.0, December 20234.1.0, June 20222.0
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2commercialcommercial infofree developer edition available
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 languageC++C and C++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux infoLinux, macOS, Windows for the developer addition
Data schemeyes infoRDF schemasyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementsSQL-like query language (GQL)yes infothrough the embedded Spark runtime
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infouser defined functions and integration of map-reduceusing Google App Engineyes
TriggersyesnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication using PaxosActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual 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.Eventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphApache ImpalaGoogle Cloud DatastoreIBM Db2 Event Store
News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

Gartner recognized Franz Inc. as a Key Neuro-Symbolic AI Provider in 2024 Hype Cycle for AI
10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Awesome AI Companies – Franz Inc.
17 July 2024

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More resources
AllegroGraphApache ImpalaGoogle Cloud DatastoreIBM Db2 Event Store
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