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DBMS > Apache Impala vs. Datomic vs. PlanetScale vs. YugabyteDB

System Properties Comparison Apache Impala vs. Datomic vs. PlanetScale vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonPlanetScale  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable, distributed, serverless MySQL database platform built on top of VitessHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score1.09
Rank#178  Overall
#82  Relational DBMS
Score2.48
Rank#108  Overall
#53  Relational DBMS
Websiteimpala.apache.orgwww.datomic.complanetscale.comwww.yugabyte.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.complanetscale.com/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectPlanetScaleYugabyte Inc.
Initial release2013201220202017
Current release4.1.0, June 20221.0.7180, July 20242.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoApache 2.0
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.
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++Java, ClojureGoC and C++
Server operating systemsLinuxAll OS with a Java VMDocker
Linux
macOS
Linux
OS X
Data schemeyesyesyesdepending on used data model
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensionsyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
JDBC
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/ODBCClojure
Java
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
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-reduceyes infoTransaction Functionsyes infoproprietary syntaxyes infosql, plpgsql, C
TriggersnoBy using transaction functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
Based 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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at shard levelDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization concept infono user groups or rolesyes
More information provided by the system vendor
Apache ImpalaDatomicPlanetScaleYugabyteDB
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 ImpalaDatomicPlanetScaleYugabyteDB
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