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DBMS > Apache Impala vs. InterSystems Caché vs. LeanXcale vs. Microsoft Azure SQL Database vs. RavenDB

System Properties Comparison Apache Impala vs. InterSystems Caché vs. LeanXcale vs. Microsoft Azure SQL Database vs. RavenDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRavenDB  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA multi-model DBMS and application serverA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesDatabase as a Service offering with high compatibility to Microsoft SQL ServerOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument storeDocument storeDocument store
Graph DBMS
Spatial DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websiteimpala.apache.orgwww.intersystems.com/­products/­cachewww.leanxcale.comazure.microsoft.com/­en-us/­products/­azure-sql/­databaseravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmldocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­azure-sqlravendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaInterSystemsLeanXcaleMicrosoftHibernating Rhinos
Initial release20131997201520102010
Current release4.1.0, June 20222018.1.4, May 2020V125.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C#
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesdepending on used data modelyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infothrough Apache DerbyyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
C
Java
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesTransact SQLyes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes, with always 3 replicas availableMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAuthorization levels configured per client per database

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More resources
Apache ImpalaInterSystems CachéLeanXcaleMicrosoft Azure SQL Database infoformerly SQL AzureRavenDB
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