DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Atos Standard Common Repository vs. eXtremeDB vs. Google Cloud Bigtable vs. TigerGraph

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. eXtremeDB vs. Google Cloud Bigtable vs. TigerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGoogle Cloud Bigtable  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 networksNatively 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.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.mcobject.comcloud.google.com/­bigtablewww.tigergraph.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docsdocs.tigergraph.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMcObjectGoogle
Initial release20132016200120152017
Current release4.1.0, June 202217038.2, 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++C++
Server operating systemsLinuxLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
Data schemeyesSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyesnoyes
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 infosupport of XML interfaces availablenono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith the option: eXtremeSQLnoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
LDAP.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindings.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesnoyes
Triggersnoyesyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionhorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesActive Replication Fabric™ 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 zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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 authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
More information provided by the system vendor
Apache ImpalaAtos Standard Common RepositoryeXtremeDBGoogle Cloud BigtableTigerGraph
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
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...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaAtos Standard Common RepositoryeXtremeDBGoogle Cloud BigtableTigerGraph
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

provided by Google News

eXtremeDB 8.4 Unveils Exciting New Features and Enhancements
13 May 2024, EE Journal

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject’s new eXtremeDB Cluster provides distributed database solution for real-time apps
20 July 2011, Embedded

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database
6 May 2015, TechCrunch

provided by Google News

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

New TigerGraph CEO Refocuses Efforts on Enterprise Customers
31 July 2023, Datanami

Aerospike takes on Neo4j and TigerGraph with launch of graph database
20 June 2023, SiliconANGLE News

provided by Google News



Share this page

Featured Products

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here