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DBMS > Apache Impala vs. RavenDB vs. SiteWhere vs. Splice Machine

System Properties Comparison Apache Impala vs. RavenDB vs. SiteWhere vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonRavenDB  Xexclude from comparisonSiteWhere  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseM2M integration platform for persisting/querying time series dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score2.68
Rank#102  Overall
#19  Document stores
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteimpala.apache.orgravendb.netgithub.com/­sitewhere/­sitewheresplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlravendb.net/­docssitewhere1.sitewhere.io/­index.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHibernating RhinosSiteWhereSplice Machine
Initial release2013201020102014
Current release4.1.0, June 20225.4, July 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3, commercial license availableOpen Source infoCommon Public Attribution License Version 1.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#JavaJava
Server operating systemsLinuxLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freepredefined schemeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (RQL)noyes
APIs and other access methodsJDBC
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
HTTP RESTJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infoJava
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAuthorization levels configured per client per databaseUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaRavenDBSiteWhereSplice Machine
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