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DBMS > Databricks vs. Hypertable vs. Ignite vs. Memcached vs. Spark SQL

System Properties Comparison Databricks vs. Hypertable vs. Ignite vs. Memcached vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonIgnite  Xexclude from comparisonMemcached  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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.An open source BigTable implementation based on distributed file systems such as HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.In-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Wide column storeKey-value store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comignite.apache.orgwww.memcached.orgspark.apache.org/­sql
Technical documentationdocs.databricks.comapacheignite.readme.io/­docsgithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksHypertable Inc.Apache Software FoundationDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release20132009201520032014
Current release0.9.8.11, March 2016Apache Ignite 2.61.6.27, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open Source infoBSD licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, .NetCScala
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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.yesyesno
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesnono
SQL infoSupport of SQLwith Databricks SQLnoANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
C++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolJDBC
ODBC
Supported programming languagesPython
R
Scala
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes (compute grid and cache interceptors can be used instead)nono
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelyes (replicated cache)none infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoSecurity Hooks for custom implementationsyes infousing SASL (Simple Authentication and Security Layer) protocolno
More information provided by the system vendor
DatabricksHypertableIgniteMemcachedSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHypertableIgniteMemcachedSpark SQL
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