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DBMS > Apache Impala vs. ArcadeDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. ArcadeDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonArcadeDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenA 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.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSWide column store
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
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteimpala.apache.orgarcadedb.comcloud.google.com/­spannerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmldocs.arcadedb.comcloud.google.com/­spanner/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaArcade DataGoogleMicrosoft
Initial release2013202120172012
Current release4.1.0, June 2022September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinuxAll OS with a Java VMhostedhosted
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language, no joinsyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
ODBC
JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCJavaGo
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication with 3 replicas for regional instances.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationship in graphsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationoptimistic locking
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.nonono
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)Access rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaArcadeDBGoogle Cloud SpannerMicrosoft Azure Table Storage
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