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DBMS > Altibase vs. Apache Druid vs. EsgynDB vs. Google Cloud Datastore vs. Microsoft Access

System Properties Comparison Altibase vs. Apache Druid vs. EsgynDB vs. Google Cloud Datastore vs. Microsoft Access

Editorial information provided by DB-Engines
NameAltibase  Xexclude from comparisonApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionAn enterprise grade, high-performance RDBMSOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#186  Overall
#87  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitealtibase.comdruid.apache.orgwww.esgyn.cncloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationgithub.com/­ALTIBASE/­Documents/­tree/­master/­Manualsdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperAltibaseApache Software Foundation and contributorsEsgynGoogleMicrosoft
Initial release19992012201520081992
Current releasev7.3, 2023, August 202329.0.1, April 20241902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercial infoOpen source edition discontinued with March 2023Open Source infoApache license v2commercialcommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++, JavaC++
Server operating systemsAIX
HP-UX
Linux
Linux
OS X
Unix
LinuxhostedWindows infoNot a real database server, but making use of DLLs
Data schemeyesyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, 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.nononono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLANSI SQL-92SQL for queryingyesSQL-like query language (GQL)yes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
Proprietary protocol
JDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C++
Java
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresstored procedures and stored functionsnoJava Stored Proceduresusing Google App Engineyes infosince Access 2010 using the ACE-engine
TriggersyesnonoCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infomanual/auto, time-basedShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integrityyesnoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003

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More resources
AltibaseApache DruidEsgynDBGoogle Cloud DatastoreMicrosoft Access
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