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DBMS > AgensGraph vs. EDB Postgres vs. Google Cloud Bigtable vs. Kinetica

System Properties Comparison AgensGraph vs. EDB Postgres vs. Google Cloud Bigtable vs. Kinetica

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitebitnine.net/­agensgraphwww.enterprisedb.comcloud.google.com/­bigtablewww.kinetica.com
Technical documentationbitnine.net/­documentationwww.enterprisedb.com/­docscloud.google.com/­bigtable/­docsdocs.kinetica.com
DeveloperBitnine Global Inc.EnterpriseDBGoogleKinetica
Initial release2016200520152012
Current release2.1, December 201814, December 20217.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infoBSD for PostgreSQL-componentscommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCC, C++
Server operating systemsLinux
OS X
Windows
Linux
Windows
hostedLinux
Data schemedepending on used data modelyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyes infostandard with numerous extensionsnoSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functions
Triggersnoyesnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioning infoby hash, list or rangeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nononoyes infoGPU vRAM or System RAM
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)Access rights for users and roles on table level

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More resources
AgensGraphEDB PostgresGoogle Cloud BigtableKinetica
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