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DBMS > atoti vs. Databricks vs. Hawkular Metrics vs. LeanXcale

System Properties Comparison atoti vs. Databricks vs. Hawkular Metrics vs. LeanXcale

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonLeanXcale  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.The 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelObject oriented DBMSDocument store
Relational DBMS
Time Series DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#242  Overall
#10  Object oriented DBMS
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Websiteatoti.iowww.databricks.comwww.hawkular.orgwww.leanxcale.com
Technical documentationdocs.atoti.iodocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperActiveViamDatabricksCommunity supported by Red HatLeanXcale
Initial release201320142015
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyes
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.yesno
Secondary indexesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)with Databricks SQLnoyes infothrough Apache Derby
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
C
Java
Scala
Server-side scripts infoStored proceduresPythonuser defined functions and aggregatesno
Triggersyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlno
More information provided by the system vendor
atotiDatabricksHawkular MetricsLeanXcale
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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atotiDatabricksHawkular MetricsLeanXcale
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