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DBMS > Databricks vs. Geode vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics

System Properties Comparison Databricks vs. Geode vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionThe 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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelDocument store
Relational DBMS
Key-value storeKey-value store
Wide column store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitewww.databricks.comgeode.apache.orgcloud.google.com/­bigtablewww.harperdb.iowww.hawkular.org
Technical documentationdocs.databricks.comgeode.apache.org/­docscloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleHarperDBCommunity supported by Red Hat
Initial release20132002201520172014
Current release1.1, February 20173.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJava
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyes
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.yesnononono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)noSQL-like data manipulation statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoCustom Functions infosince release 3.1no
Triggersyes infoCache Event Listenersnonoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeAtomic single-row operationsAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesno
More information provided by the system vendor
DatabricksGeodeGoogle Cloud BigtableHarperDBHawkular Metrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGeodeGoogle Cloud BigtableHarperDBHawkular Metrics
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