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DBMS > Hypertable vs. Ignite vs. Memcached vs. Microsoft Access vs. Spark SQL

System Properties Comparison Hypertable vs. Ignite vs. Memcached vs. Microsoft Access vs. Spark SQL

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIgnite  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.In-memory key-value store, originally intended for cachingMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeKey-value store
Relational DBMS
Key-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteignite.apache.orgwww.memcached.orgwww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sql
Technical documentationapacheignite.readme.io/­docsgithub.com/­memcached/­memcached/­wikideveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Apache Software FoundationDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftApache Software Foundation
Initial release20092015200319922014
Current release0.9.8.11, March 2016Apache Ignite 2.61.6.27, May 20241902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open Source infoBSD licensecommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, .NetCC++Scala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Unix
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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.yesno
Secondary indexesrestricted infoonly exact value or prefix value scansyesnoyesno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnoyes infobut not compliant to any SQL standardSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)noyes infosince Access 2010 using the ACE-engineno
Triggersnoyes (cache interceptors and events)noyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyes (replicated cache)none infoRepcached, a Memcached patch, provides this functionallitynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesnoyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnoSecurity Hooks for custom implementationsyes infousing SASL (Simple Authentication and Security Layer) protocolno infoa simple user-level security was built in till version Access 2003no

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More resources
HypertableIgniteMemcachedMicrosoft AccessSpark SQL
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