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DBMS > Apache Impala vs. GreptimeDB vs. Spark SQL vs. Teradata

System Properties Comparison Apache Impala vs. GreptimeDB vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGreptimeDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn open source Time Series DBMS built for increased scalability, high performance and efficiencySpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSTime Series 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
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteimpala.apache.orggreptime.comspark.apache.org/­sqlwww.teradata.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.greptime.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGreptime Inc.Apache Software FoundationTeradata
Initial release2013202220141984
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 2Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++RustScala
Server operating systemsLinuxAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
hosted
Linux
Data schemeyesschema-free, schema definition possibleyesyes
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 statementsyesSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
gRPC
HTTP API
JDBC
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC++
Erlang
Go
Java
JavaScript
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-reducePythonnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes
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 factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSimple rights management via user accountsnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaGreptimeDBSpark SQLTeradata
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaGreptimeDBSpark SQLTeradata
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