DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. DuckDB vs. Google Cloud Spanner vs. Teradata Aster

System Properties Comparison Apache Impala vs. DuckDB vs. Google Cloud Spanner vs. Teradata Aster

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Spanner  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 HadoopAn embeddable, in-process, column-oriented SQL OLAP RDBMSA 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.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Websiteimpala.apache.orgduckdb.orgcloud.google.com/­spanner
Technical documentationimpala.apache.org/­impala-docs.htmlduckdb.org/­docscloud.google.com/­spanner/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleTeradata
Initial release2013201820172005
Current release4.1.0, June 20221.0.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsLinuxserver-lesshostedLinux
Data schemeyesyesyesFlexible 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 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 infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsJDBC
ODBC
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoR packages
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication with 3 replicas for regional instances.yes 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 MapReducenoyes infousing Google Cloud Dataflowyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
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 datanoACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaDuckDBGoogle Cloud SpannerTeradata Aster
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

DuckDB promises greater stability with 1.0 release
5 June 2024, The Register

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

DuckDB 1.0 Released
4 June 2024, iProgrammer

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

provided by Google News

Google's Cloud Spanner Now Spans Continents … Like It's Supposed to Do
31 May 2024, Data Center Knowledge

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Cloud just fired a major volley at AWS as the cloud wars heat up
12 October 2023, TechRadar

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata unveils improved QueryGrid connectors
21 April 2015, CIO

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here