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DBMS > Apache Impala vs. Apache Pinot vs. Atos Standard Common Repository vs. Google Cloud Bigtable vs. TigerGraph

System Properties Comparison Apache Impala vs. Apache Pinot vs. Atos Standard Common Repository vs. Google Cloud Bigtable vs. TigerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Pinot  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Key-value store
Wide column store
Graph 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
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteimpala.apache.orgpinot.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.tigergraph.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.pinot.apache.orgcloud.google.com/­bigtable/­docsdocs.tigergraph.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation and contributorsAtos Convergence CreatorsGoogle
Initial release20132015201620152017
Current release4.1.0, June 20221.0.0, September 20231703
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialcommercial
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++JavaJavaC++
Server operating systemsLinuxAll OS with a Java JDK11 or higherLinuxhostedLinux
Data schemeyesyesSchema and schema-less with LDAP viewsschema-freeyes
Typing infopredefined data types such as float or dateyesyesoptionalnoyes
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.noyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenonoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
JDBCLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
All languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infocell divisionSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsAtomic single-row operationsACID
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Apache ImpalaApache PinotAtos Standard Common RepositoryGoogle Cloud BigtableTigerGraph
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