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DBMS > Apache Impala vs. BigchainDB vs. Google Cloud Spanner vs. HBase

System Properties Comparison Apache Impala vs. BigchainDB vs. Google Cloud Spanner vs. HBase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Wide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSDocument storeRelational DBMSWide column store
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
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websiteimpala.apache.orgwww.bigchaindb.comcloud.google.com/­spannerhbase.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­spanner/­docshbase.apache.org/­book.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2013201620172008
Current release4.1.0, June 20222.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL v3commercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++PythonJava
Server operating systemsLinuxLinuxhostedLinux
Unix
Windows infousing Cygwin
Data schemeyesschema-freeyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesnoyesoptions to bring your own types, AVRO
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 indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
ODBC
CLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCGo
Haskell
Java
JavaScript
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoCoprocessors in Java
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Apache ImpalaBigchainDBGoogle Cloud SpannerHBase
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