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DBMS > Apache Impala vs. BigchainDB vs. Google Cloud Bigtable vs. Postgres-XL vs. TerarkDB

System Properties Comparison Apache Impala vs. BigchainDB vs. Google Cloud Bigtable vs. Postgres-XL vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBigchainDB 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.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Relational DBMSKey-value store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.76
Rank#216  Overall
#36  Document stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websiteimpala.apache.orgwww.bigchaindb.comcloud.google.com/­bigtablewww.postgres-xl.orggithub.com/­bytedance/­terarkdb
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­bigtable/­docswww.postgres-xl.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleByteDance, originally Terark
Initial release2013201620152014 infosince 2012, originally named StormDB2016
Current release4.1.0, June 202210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL v3commercialOpen Source infoMozilla public licensecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++PythonCC++
Server operating systemsLinuxLinuxhostedLinux
macOS
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnonoyesno
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.nononoyes infoXML type, but no XML query functionalityno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infodistributed, parallel query executionno
APIs and other access methodsJDBC
ODBC
CLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
C++ API
Java API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Apache ImpalaBigchainDBGoogle Cloud BigtablePostgres-XLTerarkDB
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