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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBigchainDB  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 HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGoogle'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 DBMSDocument store
Key-value store
Document storeKey-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
Score0.79
Rank#212  Overall
#36  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comcloud.google.com/­bigtablewww.tigergraph.com
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­bigtable/­docsdocs.tigergraph.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsGoogle
Initial release20132016201620152017
Current release4.1.0, June 20221703
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL v3commercialcommercial
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++JavaPythonC++
Server operating systemsLinuxLinuxLinuxhostedLinux
Data schemeyesSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalnonoyes
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.noyesnonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
LDAPCLI Client
RESTful HTTP API
gRPC (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/ODBCAll languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
C#
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 nodesShardingSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factorInternal 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 MapReducenoyesyes
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 integritynonononoyes 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 datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes,with MongoDB ord RethinkDByesyes
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 authenticationyesAccess 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 ImpalaAtos Standard Common RepositoryBigchainDBGoogle Cloud BigtableTigerGraph
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