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DBMS > BoltDB vs. Databricks vs. GridGain vs. Sphinx vs. Teradata Aster

System Properties Comparison BoltDB vs. Databricks vs. GridGain vs. Sphinx vs. Teradata Aster

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAn embedded key-value store for Go.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.GridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeDocument store
Relational DBMS
Key-value store
Relational DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegithub.com/­boltdb/­boltwww.databricks.comwww.gridgain.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperDatabricksGridGain Systems, Inc.Sphinx Technologies Inc.Teradata
Initial release20132013200720012005
Current releaseGridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, C++, .NetC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.noyesyesyes infoin Aster File Store
Secondary indexesnoyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnowith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGoPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)noR packages
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes (replicated cache)noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)noyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standard
More information provided by the system vendor
BoltDBDatabricksGridGainSphinxTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
BoltDBDatabricksGridGainSphinxTeradata Aster
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