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DBMS > Apache Impala vs. DuckDB vs. Sphinx vs. YugabyteDB

System Properties Comparison Apache Impala vs. DuckDB vs. Sphinx vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDuckDB  Xexclude from comparisonSphinx  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, in-process, column-oriented SQL OLAP RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeDocument store
Wide column 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
Score5.95
Rank#55  Overall
#5  Search engines
Score2.63
Rank#109  Overall
#53  Relational DBMS
Websiteimpala.apache.orgduckdb.orgsphinxsearch.comwww.yugabyte.com
Technical documentationimpala.apache.org/­impala-docs.htmlduckdb.org/­docssphinxsearch.com/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSphinx Technologies Inc.Yugabyte Inc.
Initial release2013201820012017
Current release4.1.0, June 20221.0.0, June 20243.5.1, February 20232.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC++C++C++C and C++
Server operating systemsLinuxserver-lessFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Data schemeyesyesyesdepending on used data model
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.nonono
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (SphinxQL)yes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Proprietary protocolJDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes infosql, plpgsql, C
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnonoyes
More information provided by the system vendor
Apache ImpalaDuckDBSphinxYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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Apache ImpalaDuckDBSphinxYugabyteDB
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