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DBMS > Apache Impala vs. Google Cloud Spanner vs. Spark SQL vs. Teradata

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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.Spark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­spannerspark.apache.org/­sqlwww.teradata.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleApache Software FoundationTeradata
Initial release2013201720141984
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinuxhostedLinux
OS X
Windows
hosted
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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
Secondary indexesyesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationnoACID
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache ImpalaGoogle Cloud SpannerSpark SQLTeradata
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