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DBMS > Alibaba Cloud MaxCompute vs. Apache Druid vs. Geode vs. IRONdb vs. Spark SQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Druid vs. Geode vs. IRONdb vs. Spark SQL

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache Druid  Xexclude from comparisonGeode  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputedruid.apache.orggeode.apache.orgwww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedruid.apache.org/­docs/­latest/­designgeode.apache.org/­docsdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAlibabaApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Circonus LLC.Apache Software Foundation
Initial release20162012200220172014
Current release29.0.1, April 20241.1, February 2017V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++Scala
Server operating systemshostedLinux
OS X
Unix
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxLinux
OS X
Windows
Data schemeyesyes infoschema-less columns are supportedschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histogramsyes
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.nonononono
Secondary indexesnoyesnonono
SQL infoSupport of SQLSQL-like query languageSQL for queryingSQL-like query language (OQL)SQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
RESTful HTTP/JSON API
Java Client API
Memcached protocol
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesJavaClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javanouser defined functionsyes, in Luano
Triggersnonoyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infomanual/auto, time-basedShardingAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes, via HDFS, S3 or other storage enginesMulti-source replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyes, on a single nodenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights per client and object definablenono

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More resources
Alibaba Cloud MaxComputeApache DruidGeodeIRONdbSpark SQL
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