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DBMS > Apache Impala vs. GBase vs. Google Cloud Bigtable vs. Teradata Aster

System Properties Comparison Apache Impala vs. GBase vs. Google Cloud Bigtable vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational 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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteimpala.apache.orgwww.gbase.cncloud.google.com/­bigtable
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeneral Data Technology Co., Ltd.GoogleTeradata
Initial release2013200420152005
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, Python
Server operating systemsLinuxLinuxhostedLinux
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsStandard with numerous extensionsnoyes
APIs and other access methodsJDBC
ODBC
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC#C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoR packages
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic 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.nonono
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-standard

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More resources
Apache ImpalaGBaseGoogle Cloud BigtableTeradata Aster
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