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DBMS > Databricks vs. GridGain vs. Informix vs. XTDB

System Properties Comparison Databricks vs. GridGain vs. Informix vs. XTDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonInformix  Xexclude from comparisonXTDB infoformerly named Crux  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.GridGain is an in-memory computing platform, built on Apache IgniteA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBDocument store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitewww.databricks.comwww.gridgain.comwww.ibm.com/­products/­informixgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
www.xtdb.com/­docs
DeveloperDatabricksGridGain Systems, Inc.IBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Juxt Ltd.
Initial release2013200719842019
Current releaseGridGain 8.5.114.10.FC5, November 20201.19, September 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC, C++ and JavaClojure
Server operating systemshostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes, extensible-data-notation format
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 indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyeslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP REST
JDBC
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yesno
Triggersyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)Multi-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsUsers with fine-grained authentication, authorization, and auditing controls
More information provided by the system vendor
DatabricksGridGainInformixXTDB infoformerly named Crux
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGridGainInformixXTDB infoformerly named Crux
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