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DBMS > Apache Impala vs. BigchainDB vs. Google Cloud Bigtable vs. Postgres-XL vs. Titan

System Properties Comparison Apache Impala vs. BigchainDB vs. Google Cloud Bigtable vs. Postgres-XL vs. Titan

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAnalytic DBMS for HadoopBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Relational DBMSGraph 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
Score0.85
Rank#208  Overall
#35  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websiteimpala.apache.orgwww.bigchaindb.comcloud.google.com/­bigtablewww.postgres-xl.orggithub.com/­thinkaurelius/­titan
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­bigtable/­docswww.postgres-xl.org/­documentationgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleAurelius, owned by DataStax
Initial release2013201620152014 infosince 2012, originally named StormDB2012
Current release4.1.0, June 202210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL v3commercialOpen Source infoMozilla public licenseOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++PythonCJava
Server operating systemsLinuxLinuxhostedLinux
macOS
Linux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infodistributed, parallel query executionno
APIs and other access methodsJDBC
ODBC
CLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBCGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functionsyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
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 KerberosyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
Apache ImpalaBigchainDBGoogle Cloud BigtablePostgres-XLTitan
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