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DBMS > Apache Impala vs. HugeGraph vs. Splice Machine vs. VoltDB

System Properties Comparison Apache Impala vs. HugeGraph vs. Splice Machine vs. VoltDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHugeGraph  Xexclude from comparisonSplice Machine  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA fast-speed and highly-scalable Graph DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSGraph DBMSRelational DBMSRelational DBMS
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
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websiteimpala.apache.orggithub.com/­hugegraph
hugegraph.apache.org
splicemachine.comwww.voltdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlhugegraph.apache.org/­docssplicemachine.com/­how-it-worksdocs.voltdb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaiduSplice MachineVoltDB Inc.
Initial release2013201820142010
Current release4.1.0, June 20220.93.1, March 202111.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaJava, C++
Server operating systemsLinuxLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
OS X infofor development
Data schemeyesyesyesyes
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.nono
Secondary indexesyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCGroovy
Java
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsyes infoJavaJava
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducevia hugegraph-sparkYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers, roles and permissionsAccess rights for users, groups and roles according to SQL-standardUsers and roles with access to stored procedures

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More resources
Apache ImpalaHugeGraphSplice MachineVoltDB
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