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DBMS > Apache Pinot vs. EsgynDB vs. Hive vs. HugeGraph vs. Microsoft Azure Table Storage

System Properties Comparison Apache Pinot vs. EsgynDB vs. Hive vs. HugeGraph vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonEsgynDB  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitepinot.apache.orgwww.esgyn.cnhive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.pinot.apache.orgcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperApache Software Foundation and contributorsEsgynApache Software Foundation infoinitially developed by FacebookBaiduMicrosoft
Initial release20152015201220182012
Current release1.0.0, September 20233.1.3, April 20220.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJavaJava
Server operating systemsAll OS with a Java JDK11 or higherLinuxAll OS with a Java VMLinux
macOS
Unix
hosted
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonono
Secondary indexesyesyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statementsnono
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languagesGo
Java
Python
All languages supporting JDBC/ODBC/ADO.NetC++
Java
PHP
Python
Groovy
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducevia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesUsers, roles and permissionsAccess rights based on private key authentication or shared access signatures

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More resources
Apache PinotEsgynDBHiveHugeGraphMicrosoft Azure Table Storage
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