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DBMS > Apache Impala vs. Google Cloud Datastore vs. JanusGraph vs. TDSQL for MySQL vs. Yaacomo

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. JanusGraph vs. TDSQL for MySQL vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument storeGraph DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­datastorejanusgraph.orgwww.tencentcloud.com/­products/­dcdbyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsdocs.janusgraph.orgwww.tencentcloud.com/­document/­product/­1042
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleLinux Foundation; originally developed as Titan by AureliusTencentQ2WEB GmbH
Initial release20132008201720132009
Current release4.1.0, June 20220.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
hostedAndroid
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)noyesyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyesyes
TriggersnoCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Automatic shardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosyesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph ServerUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache ImpalaGoogle Cloud DatastoreJanusGraph infosuccessor of TitanTDSQL for MySQLYaacomo
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