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DBMS > Apache Impala vs. Databricks vs. Memgraph

System Properties Comparison Apache Impala vs. Databricks vs. Memgraph

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonMemgraph  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.An open source graph database built for real-time streaming and compatible with Neo4j
Primary database modelRelational DBMSDocument store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score11.68
Rank#41  Overall
#25  Relational DBMS
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score2.54
Rank#98  Overall
#8  Graph DBMS
Websiteimpala.apache.orgwww.databricks.commemgraph.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.commemgraph.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksMemgraph Ltd
Initial release201320132017
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSL 1.1; commercial license for enterprise edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++
Server operating systemsLinuxhostedLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free and schema-optional
Typing infopredefined data types such as float or dateyesyes
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.noyesno
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregates
Triggersno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infodynamic graph partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infowith snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith periodic snapshot and write-ahead logging (WAL) of changes
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 KerberosUsers, roles and permissions

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More resources
Apache ImpalaDatabricksMemgraph
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