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DBMS > Databricks vs. Drizzle vs. Geode vs. Google Cloud Bigtable vs. Heroic

System Properties Comparison Databricks vs. Drizzle vs. Geode vs. Google Cloud Bigtable vs. Heroic

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHeroic  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeKey-value store
Wide column store
Time 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Websitewww.databricks.comgeode.apache.orgcloud.google.com/­bigtablegithub.com/­spotify/­heroic
Technical documentationdocs.databricks.comgeode.apache.org/­docscloud.google.com/­bigtable/­docsspotify.github.io/­heroic
DeveloperDatabricksDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleSpotify
Initial release20132008200220152014
Current release7.2.4, September 20121.1, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemshostedFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-freeschema-free
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.yesnonono
Secondary indexesyesyesnonoyes infovia Elasticsearch
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsSQL-like query language (OQL)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsnono
Triggersno infohooks for callbacks inside the server can be used.yes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeAtomic single-row operationsno
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.noyesnono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
DatabricksDrizzleGeodeGoogle Cloud BigtableHeroic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleGeodeGoogle Cloud BigtableHeroic
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