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DBMS > Apache Impala vs. DuckDB vs. Google Cloud Datastore vs. TimesTen

System Properties Comparison Apache Impala vs. DuckDB vs. Google Cloud Datastore vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score5.61
Rank#60  Overall
#34  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteimpala.apache.orgduckdb.orgcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationimpala.apache.org/­impala-docs.htmlduckdb.org/­docscloud.google.com/­datastore/­docsdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2013201820081998
Current release4.1.0, June 20221.0.0, June 2024Release 22.1
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-lesshostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (GQL)yes
APIs and other access methodsJDBC
ODBC
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenousing Google App EnginePL/SQL
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
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

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More resources
Apache ImpalaDuckDBGoogle Cloud DatastoreTimesTen
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