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DBMS > atoti vs. Google BigQuery vs. Hazelcast vs. Linter vs. PostgreSQL

System Properties Comparison atoti vs. Google BigQuery vs. Hazelcast vs. Linter vs. PostgreSQL

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Large scale data warehouse service with append-only tablesA widely adopted in-memory data gridRDBMS for high security requirementsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelObject oriented DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteatoti.iocloud.google.com/­bigqueryhazelcast.comlinter.ruwww.postgresql.org
Technical documentationdocs.atoti.iocloud.google.com/­bigquery/­docshazelcast.org/­imdg/­docswww.postgresql.org/­docs
DeveloperActiveViamGoogleHazelcastrelex.ruPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2010200819901989 info1989: Postgres, 1996: PostgreSQL
Current release5.3.6, November 202316.3, May 2024
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C
Server operating systemshostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infothe object must implement a serialization strategynoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnoyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesSQL-like query languageyesyes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP/JSON APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresPythonuser defined functions infoin JavaScriptyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardingnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnoyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
atotiGoogle BigQueryHazelcastLinterPostgreSQL
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