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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Google Cloud Spanner vs. ReductStore vs. TigerGraph

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Google Cloud Spanner vs. ReductStore vs. TigerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonReductStore  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 networksA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSTime Series DBMSGraph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­spannergithub.com/­reductstore
www.reduct.store
www.tigergraph.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docswww.reduct.store/­docsdocs.tigergraph.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsGoogleReductStore LLC
Initial release20132016201720232017
Current release4.1.0, June 202217031.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoBusiness Source License 1.1commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++, RustC++
Server operating systemsLinuxLinuxhostedDocker
Linux
macOS
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.noyesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoQuery statements complying to ANSI 2011SQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
LDAPgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsGo
Java
JavaScript (Node.js)
Python
C++
JavaScript (Node.js)
Python
Rust
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infoStrict serializable isolationACID
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Apache ImpalaAtos Standard Common RepositoryGoogle Cloud SpannerReductStoreTigerGraph
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