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DBMS > Apache Impala vs. Databricks vs. EsgynDB vs. RavenDB vs. Transbase

System Properties Comparison Apache Impala vs. Databricks vs. EsgynDB vs. RavenDB vs. Transbase

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonRavenDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comwww.esgyn.cnravendb.netwww.transaction.de/­en/­products/­transbase.html
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comravendb.net/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksEsgynHibernating RhinosTransaction Software GmbH
Initial release20132013201520101987
Current release4.1.0, June 20225.4, July 2022Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoAGPL version 3, commercial license availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaC#C and C++
Server operating systemsLinuxhostedLinuxLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
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.noyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyesSQL-like query language (RQL)yes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
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
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesJava Stored Proceduresyesyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication between multi datacentersMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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.Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, Cluster-wide transaction availableyes
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAuthorization levels configured per client per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDatabricksEsgynDBRavenDBTransbase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksEsgynDBRavenDBTransbase
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