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DBMS > Apache Impala vs. dBASE vs. Google Cloud Datastore vs. HugeGraph vs. mSQL

System Properties Comparison Apache Impala vs. dBASE vs. Google Cloud Datastore vs. HugeGraph vs. mSQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopdBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelRelational DBMSRelational DBMSDocument storeGraph DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score10.34
Rank#44  Overall
#28  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Websiteimpala.apache.orgwww.dbase.comcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
hughestech.com.au/­products/­msql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.dbase.com/­support/­knowledgebasecloud.google.com/­datastore/­docshugegraph.apache.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAsthon TateGoogleBaiduHughes Technologies
Initial release20131979200820181994
Current release4.1.0, June 2022dBASE 2019, 20190.94.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2.0commercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC
Server operating systemsLinuxDOS infodBase Classic
Windows infodBase Pro
hostedLinux
macOS
Unix
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language (GQL)noA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
ODBC
none infoThe IDE can access other DBMS or ODBC-sources.gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCdBase proprietary IDE.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno infoThe IDE can access stored procedures in other database systems.using Google App Engineasynchronous Gremlin script jobsno
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 Consistencynone
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infonot for dBase internal data, but IDE does support transactions when accessing external DBMSACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsno

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More resources
Apache ImpaladBASEGoogle Cloud DatastoreHugeGraphmSQL infoMini SQL
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