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DBMS > Apache Impala vs. Datomic vs. EXASOL vs. Google Cloud Spanner

System Properties Comparison Apache Impala vs. Datomic vs. EXASOL vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A 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.
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational 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
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score1.66
Rank#138  Overall
#64  Relational DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Websiteimpala.apache.orgwww.datomic.comwww.exasol.comcloud.google.com/­spanner
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comwww.exasol.com/­resourcescloud.google.com/­spanner/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectExasolGoogle
Initial release2013201220002017
Current release4.1.0, June 20221.0.7180, July 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, Clojure
Server operating systemsLinuxAll OS with a Java VMhosted
Data schemeyesyesyesyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infoQuery statements complying to ANSI 2011
APIs and other access methodsJDBC
ODBC
RESTful HTTP API.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
Java
Lua
Python
R
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsuser defined functionsno
TriggersnoBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infoHadoop integrationyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 KerberosnoAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache ImpalaDatomicEXASOLGoogle Cloud Spanner
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