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DBMS > Databricks vs. Google Cloud Datastore vs. Ignite vs. TDSQL for MySQL

System Properties Comparison Databricks vs. Google Cloud Datastore vs. Ignite vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonTDSQL for MySQL  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelDocument store
Relational DBMS
Document storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial 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
Score4.36
Rank#72  Overall
#12  Document stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitewww.databricks.comcloud.google.com/­datastoreignite.apache.orgwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsapacheignite.readme.io/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperDatabricksGoogleApache Software FoundationTencent
Initial release2013200820152013
Current releaseApache Ignite 2.6
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .Net
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsUsers with fine-grained authorization concept
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreIgniteTDSQL for MySQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGoogle Cloud DatastoreIgniteTDSQL for MySQL
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