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DBMS > Databricks vs. Google Cloud Spanner vs. GridGain vs. Machbase Neo vs. Sphinx

System Properties Comparison Databricks vs. Google Cloud Spanner vs. GridGain vs. Machbase Neo vs. Sphinx

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGridGain  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSphinx  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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.GridGain is an in-memory computing platform, built on Apache IgniteTimeSeries DBMS for AIoT and BigDataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Time Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.17
Rank#337  Overall
#30  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.databricks.comcloud.google.com/­spannerwww.gridgain.commachbase.comsphinxsearch.com
Technical documentationdocs.databricks.comcloud.google.com/­spanner/­docswww.gridgain.com/­docs/­index.htmlmachbase.com/­dbmssphinxsearch.com/­docs
DeveloperDatabricksGoogleGridGain Systems, Inc.MachbaseSphinx Technologies Inc.
Initial release20132017200720132001
Current releaseGridGain 8.5.1V8.0, August 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree test version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetCC++
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yesnoyesno
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLyes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
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 nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.yes (replicated cache)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infovolatile and lookup table
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationssimple password-based access controlno
More information provided by the system vendor
DatabricksGoogle Cloud SpannerGridGainMachbase Neo infoFormer name was InfinifluxSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGoogle Cloud SpannerGridGainMachbase Neo infoFormer name was InfinifluxSphinx
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