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DBMS > eXtremeDB vs. Google Cloud Bigtable vs. Ignite vs. Spark SQL

System Properties Comparison eXtremeDB vs. Google Cloud Bigtable vs. Ignite vs. Spark SQL

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.mcobject.comcloud.google.com/­bigtableignite.apache.orgspark.apache.org/­sql
Technical documentationwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMcObjectGoogleApache Software FoundationApache Software Foundation
Initial release2001201520152014
Current release8.2, 2021Apache Ignite 2.63.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++, Java, .NetScala
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.no infosupport of XML interfaces availablenoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)no
Triggersyes infoby defining eventsnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Internal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno
More information provided by the system vendor
eXtremeDBGoogle Cloud BigtableIgniteSpark SQL
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBGoogle Cloud BigtableIgniteSpark SQL
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