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DBMS > Apache Impala vs. Bangdb vs. Graph Engine vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. Bangdb vs. Graph Engine vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteimpala.apache.orgbangdb.comwww.graphengine.ioazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.comwww.graphengine.io/­docs/­manual
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBMicrosoftMicrosoft
Initial release2013201220102012
Current release4.1.0, June 2022BangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD 3Open Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++.NET and C
Server operating systemsLinuxLinux.NEThosted
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL like support with command line toolnono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
C#
C++
F#
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnoyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmhorizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable consistency, set CAP knob accordinglyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as welloptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modeyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)Access rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaBangdbGraph Engine infoformer name: TrinityMicrosoft Azure Table Storage
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