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DBMS > Apache Impala vs. Atos Standard Common Repository vs. GigaSpaces vs. Heroic vs. TigerGraph

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. GigaSpaces vs. Heroic vs. TigerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHeroic  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSGraph DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comgithub.com/­spotify/­heroicwww.tigergraph.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmlspotify.github.io/­heroicdocs.tigergraph.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsGigaspaces TechnologiesSpotify
Initial release20132016200020142017
Current release4.1.0, June 2022170315.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercial
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++JavaJava, C++, .NetJavaC++
Server operating systemsLinuxLinuxLinux
macOS
Solaris
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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.noyesno infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-99 for query and DML statementsnoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
LDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindings.Net
C++
Java
Python
Scala
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesnoyes
Triggersnoyesyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDnoACID
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.noyesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationRole-based access controlRole-based access control

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More resources
Apache ImpalaAtos Standard Common RepositoryGigaSpacesHeroicTigerGraph
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