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DBMS > Apache Impala vs. etcd vs. Microsoft Azure Table Storage vs. TimesTen vs. XTDB

System Properties Comparison Apache Impala vs. etcd vs. Microsoft Azure Table Storage vs. TimesTen vs. XTDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTimesTen  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed reliable key-value storeA Wide Column Store for rapid development using massive semi-structured datasetsIn-Memory RDBMS compatible to OracleA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMSDocument store
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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score1.31
Rank#163  Overall
#74  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­technologies/­related/­timesten.htmlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.oracle.com/­database/­timesten-18.1www.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Juxt Ltd.
Initial release2013201219982019
Current release4.1.0, June 20223.4, August 201911 Release 2 (11.2.2.8.0)1.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoClojure
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes, extensible-data-notation format
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 indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyeslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
gRPC
JSON over HTTP
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
PL/SQL
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoPL/SQLno
Triggersnoyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpointsyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
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 KerberosnoAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaetcdMicrosoft Azure Table StorageTimesTenXTDB infoformerly named Crux
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